Journal of Intelligent & Fuzzy Systems - Volume 40, issue 4

Authors: Cui, Di

Article Type: Research Article

Abstract: Image segmentation is very important for various fields. With the development of computer technology, computer technology has become more and more effective for image segmentation, and it is studied on the basis of partial differential equations. The curve representation method in plane differential geometry is expounded, with the SegNet-v2 segmentation model analyzed and tested in medical image segmentation. The test results show that the partial differential equation image segmentation algorithm can achieve more accurate segmentation, especially in medical image segmentation, which can achieve good results, and it is worth in practice to further promote.

Keywords: Partial differential equation, image segmentation, algorithm analysis

DOI: 10.3233/JIFS-189434

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 5945-5952, 2021

Authors: Wu, Manxia | Wang, Wen

Article Type: Research Article

Abstract: A large number of high slopes will be formed in the construction of expressways in many mountainous areas, which is very unfavorable to the construction of local expressways. Effective monitoring methods are essential to solving these problems, and the Internet of Things technology is a good dynamic monitoring method. Therefore, it is necessary to carry out research on the dynamic monitoring system of rock and soil high slope based on the Internet of Things perception. The purpose of this article is to solve the problem of dynamic monitoring of high slopes, taking highway slopes in Chongqing as an example, making …full use of the literature method, field investigation method, regression analysis method, time series analysis method, and theoretical analysis method. Through real-time monitoring of the entire process of rock and soil high slope construction in different locations in a certain area in the southwest, and continuously adjusting and verifying the monitoring situation and solving related problems, the high slope instability at this point was accurately monitored And at any time find the weak links in the construction process of high slopes, and further find its potential quality and safety risks, and then establish a comprehensive monitoring system and early warning system. The research results show that this comprehensive monitoring and early warning system improves the accuracy of early warning and monitoring from qualitative judgment to quantitative analysis and from macro to micro monitoring, and can provide a reference for other types of projects. Show more

Keywords: Internet of things, high slope, dynamic monitoring, geotechnical environment

DOI: 10.3233/JIFS-189435

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 5953-5962, 2021

Authors: Tang, Guanghai | Zeng, Hui

Article Type: Research Article

Abstract: Cloud computing, as a product of the fusion and development of computer technology and Internet technology, not only realized the innovation of IT technology but also A major revolution in the IT business model will bring unprecedented and profound changes to the information industry. The main purpose of this article is to study the collaborative management and control method of blockchain in a cloud computing environment. This article mainly uses the blockchain consensus algorithm to analyze and research the blocking technology in the logistics supply chain, and solves the supplier’s benefit formula step by step; also uses the CloudBTF algorithm, …Max-min algorithm, FCFS of cloud computing Algorithm, and compare the efficiency and security of the three methods to get the most conducive to the collaborative management and control of the blockchain. The experimental results of this paper show that blockchain collaborative management in a cloud computing environment can greatly improve the security of massive data storage and the collaborative distribution of data. Among them, the use of cloud computing platform priority algorithms can improve system load balancing by up to 12%, while Using the cloud computing platform FCFS algorithm can improve system load balancing by up to 15%. Show more

Keywords: Cloud computing, blockchain control, collaborative management, control method, cloud BFT algorithm

DOI: 10.3233/JIFS-189436

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 5963-5973, 2021

Authors: Liu, Shuqiang | Zhao, Dawei

Article Type: Research Article

Abstract: In general, there are a lot of uncertainties in uncertain information, natural language, and human knowledge. The conclusion can be better deduced by using an approximate reasoning method, while a fuzzy intelligent system can deal with uncertain data and rule evaluation information systems. In order to better explore diffusion and economic growth, this paper constructs a fuzzy intelligent system based on the DSGE model and uses this system to analyze diffusion and economic growth. In order to verify the feasibility of this system, we test the response time and accuracy of the system. In addition, we also use the system …to simulate diffusion and economic growth. The results show that with the increase of the task amount, the gap between the actual response time and the expected response time of the fuzzy intelligent system based on the DSGE model increases. When the task quantity is 20, the expected response time is 2.31 and the actual response time is 2.24. When the task quantity is 40, the expected response time is 2.5 and the actual response time is 2.36. The larger the task quantity is, the faster the response time of a fuzzy intelligent system based on the DSEG model is. Therefore, the fuzzy intelligent system based on the DSEG model has good performance and can analyze diffusion and economic growth well. Show more

Keywords: DSGE model, fuzzy intelligence system, system performance, diffusion, and economic growth

DOI: 10.3233/JIFS-189437

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 5975-5983, 2021

Authors: Wang, Linlin

Article Type: Research Article

Abstract: With the continuous development of computer science and technology, symbol recognition systems may be converted from two-dimensional space to three-dimensional space. Therefore, this article mainly introduces the symbol recognition system based on 3D stereo vision. The three-dimensional image is taken by the visual coordinate measuring machine in two places on the left and right. Perform binocular stereo matching on the edge of the feature points of the two images. A corner detection algorithm combining SUSAN and Harris is used to detect the left and right camera calibration templates. The two-dimensional coordinate points of the object are determined by the image …stereo matching module, and the three-dimensional discrete coordinate points of the object space can be obtained according to the transformation relationship between the image coordinates and the actual object coordinates. Then draw the three-dimensional model of the object through the three-dimensional drawing software. Experimental data shows that the logic resources and memory resources occupied by image preprocessing account for 30.4% and 27.4% of the entire system, respectively. The results show that the system can calibrate the internal and external parameters of the camera. In this way, the camera calibration result will be more accurate and the range will be wider. At the same time, it can effectively make up for the shortcomings of traditional modeling techniques to ensure the measurement accuracy of the detection system. Show more

Keywords: Symbol recognition system, 3d reconstruction, binocular stereo vision, feature extraction, stereo matching

DOI: 10.3233/JIFS-189438

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 5985-5994, 2021

Authors: Bian, Fei | Wang, Xuansheng

Article Type: Research Article

Abstract: School enterprise cooperation is of great strategic significance to China’s manufacturing industry. The Party Central Committee has repeatedly proposed to strengthen the integration of industry and education and deepen the cooperation between schools and enterprises. In recent years, experts and scholars at home and abroad have been from different perspectives, although they have achieved fruitful results, there are also problems such as insufficient attention to theoretical research, relatively backward research, narrow research scope, and so on. In view of this phenomenon, this paper will study a new school-enterprise cooperation mechanism based on the improved decision tree algorithm. The research of …this paper is divided into three parts. First, after analyzing the advantages and disadvantages of the algorithm, the algorithm of the decision tree is improved, which makes the improved algorithm more suitable for the field of school-enterprise cooperation. Then, based on cloud computing and intelligence, this paper establishes a new model of school-enterprise cooperation platform, which solves some problems of data management and information exchange in school-enterprise cooperation. Finally, in order to make the cooperation mechanism of this paper better used in practice, this paper builds an online and offline hybrid training base, hoping to make the cooperation between schools and enterprises closer through the training base. In order to test the effect of the cooperation model, this paper takes school as the experimental model. After investigation and research, it is believed that thanks to the school-enterprise cooperation mechanism in this paper, the cooperative enterprise of school has been greatly improved in the past three years, and the willingness of enterprises to cooperate has become more and more strong. No matter students, teachers, or enterprises are reaping huge benefits under this cooperation mechanism, it is a suit for extensive promotion The school-enterprise cooperation mechanism of Guangyun. Show more

Keywords: Improved decision tree algorithm, school-enterprise cooperation, cloud computing, combination of production and learning

DOI: 10.3233/JIFS-189439

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 5995-6005, 2021

Authors: Chen, Zhuo | Chen, Ruoxi | Chen, Songtao

Article Type: Research Article

Abstract: With the development of urbanization, the application of GIS technology is more and more extensive. This study mainly discusses the development of urban planning intelligent management information system based on GIS. To design and build a rule-detailed spatial data model, provide the physical model and the data model corresponding to the logical layer from top to bottom in all steps, based on the attribute information stored in the Geodatabase model. According to the parameters set, connect to the database through the Oracle Connection class. The defined query criteria are converted into SQL statements that are executed using the Oracle Command …class. Multi-source data integration middleware integrates various data formats with a GIS software format conversion tool or direct reading tool and then uses the geometric encoding semantics of data dictionary to represent the integrated data of system data model after merging. Property queries use the interactive search function for properties and spatial information to query the land use index for a particular area of the chart. If there is a scene roaming request from the input device, the 3D scene needs to be adjusted according to the input. Display the scene effects of a 3D virtual demonstration on a computer monitor. Start the GIS management operation function to deal with the case, and realize the user’s management of the urban planning system function with the concept of stratification. Fuzzy recognition mode is applied to identify the degree of the environmental impact of eco-city planning. The impact of urban planning on the environment is H ≈ 0.11 (0.1 < H < 1), which meets the expected standard. The results show that the system demand evaluation designed in this study is good, and the overall operation of the system is relatively stable, which plays a promoting role in urban planning. Show more

Keywords: GIS technology, urban planning, intelligent management, system research

DOI: 10.3233/JIFS-189440

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 6007-6016, 2021

Authors: Ding, Qiaoying

Article Type: Research Article

Abstract: The financial market is changing rapidly. Since joining the WTO, our country’s financial companies have faced pressure from dual competition at domestic and abroad. The complex internal and external environment has forced financial enterprise managers to improve risk prevention awareness, early warning and monitoring, so as to responding to emergencies and challenges in the financial market. However, traditional forecasting and analysis methods have problems such as large workload, low efficiency, and low accuracy. Therefore, this article applies intelligent computing to the forecast of financial markets, using related concepts of fuzzy theory and Internet intelligent technology, and proposes to establish a …model system for financial enterprise risk early warning management and intelligent real-time monitoring based on fuzzy theory. This article first collected a large amount of data through the literature investigation method, and made a systematic and complete introduction to the related theoretical concepts of fuzzy theory and financial risk early-warning management, has laid a sufficient theoretical foundation for the subsequent exploration of the application of fuzzy theory in financial enterprise risk early warning management and intelligent real-time systems; Then a fuzzy comprehensive evaluation method that combines the analytic hierarchy process and fuzzy evaluation method is proposed, taking a listed company mainly engaged in automobile sales in our province as a case, the company’s financial risk management and modeling experiment of the intelligent real-time system; Finally quoted specific cases again, used the fuzzy comprehensive evaluation method to carry out risk warning and evaluation on the PPP projects of private enterprises in our province, and concluded that the project risk score is between 20-60, which is meet the severe-medium range in the risk level. Research shows that the use of fuzzy theory and modern network technology can make more accurate warnings and assessments of potential and apparent risks of financial enterprises, greatly improving the safety of financial enterprise management and reducing the losses caused by various risks. Show more

Keywords: Fuzzy theory, financial enterprise, risk early warning management, intelligent real-time system, monitoring and prevention

DOI: 10.3233/JIFS-189441

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 6017-6027, 2021

Authors: Song, Chunhuan | Qian, Fucai

Article Type: Research Article

Abstract: With its unique array arrangement, the detection system radar has both space diversity gain and waveform diversity gain, and is currently recognized as a stealth target buster. The detection system radar is applied to a high-speed moving platform. Using distributed cooperative detection technology, non-coherent fusion detection based on signals can further improve the detection of stealthy targets. Aiming at the high-speed motion radar signal processing algorithm, this paper mainly studies the following three aspects: the first content is the analysis of the waveform characteristics: the basic principles and characteristics of the radar are explained; then the three orthogonal waveforms commonly …used in the radar are introduced, including Stepwise frequency division chirp signal, quadrature phase coded signal and mixed-signal; the second content detects radar targets and analyzes the correlation between the scattering coefficients of different radar channels; for scenarios where the scattering coefficients between the channels are non-coherent Introduced two kinds of non-coherent fusion detectors based on generalized likelihood ratio algorithm: centralized detector and double threshold detector; the third content radar multi-target pairing is aimed at the problem of radar multi-target pairing with large inertial navigation error. A multi-target pairing algorithm that uses target delay information and combines the radar’s multi-channel information redundancy characteristics is presented. An expression for judging the correctness of target pairing is derived, and the target pairing steps are given. The relationship between the amount of algorithm operation and the number of radar stations and the number of targets is analyzed in conclusion. Show more

Keywords: High-speed motion platform, generalized likelihood ratio based, orthogonal waveform, non-coherent fusion detection

DOI: 10.3233/JIFS-189442

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 6029-6038, 2021

Authors: Yuan, Zhiqian | Jin, Chaoyang | Chen, Zhaojun

Article Type: Research Article

Abstract: In recent years, with the rapid development of computer technology, the need for barrier-free communication between people of all countries have become more and more urgent. Therefore, it is extremely important to establish a high translation accuracy and high-quality English translation system. At present, Although the various English translation systems on the market have solved the communication problems between different languages to a certain extent, there are a series of problems such as language translation ambiguity and inaccurate use of words in translation methods, in order to improve English The translation accuracy of the translation system can improve the quality …of the English translation system. This paper proposes a language analysis study of the English translation system based on fuzzy algorithms. The research of this paper firmly grasps the analysis and understanding of the language, analyzes it from the corpus, vocabulary, syntax, and translation characteristics, and fully understands its language characteristics, so as to eliminate the semantic understanding ambiguity in the translation process to a certain extent. Thereby improving the accuracy of the translation. The English translation system designed in this paper includes an image input module and an image recognition module, so the Gaussian blur algorithm is used for processing. The Gaussian blur algorithm can retain edge information in the edge area where the pixel value of the image changes sharply, and can effectively remove noise and enhance the image effect. Therefore, this article uses fuzzy algorithm-based English translation system language analysis research, first analyze the English language characteristics, and then use Gaussian fuzzy algorithm to denoise the image in the translation system, and then display the image recognition results. Show more

Keywords: English translation system, language analysis research, fuzzy algorithm

DOI: 10.3233/JIFS-189443

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 6039-6047, 2021

Authors: Wang, Yingying | Zhang, Yongzhi

Article Type: Research Article

Abstract: Tennis is a set of sports and entertainment and a sports activity, since 2014, tennis in China has been another rapid development. With the development of economy and technology, tennis training mode has been further optimized and reformed. At present, tennis training robot is the mainstream way to train athletes. However, there are some defects in the current tennis training robots, such as the low accuracy of human motion real-time evaluation, and the lack of stability. Therefore, this paper puts forward the related research on the real-time evaluation algorithm of human motion in tennis training robots, hoping to make up …for the deficiency in this field. The research of this paper is mainly divided into four parts. The first part is to analyze the current situation of technology research in this field and put forward the idea of this paper by analyzing the shortcomings of the existing technology. The second part is the related basic theory research; this part deeply studies the core theory of tennis training and intelligent training robot, which provides a theoretical basis for the realization of the optimization scheme. The third part is the design and implementation of a real-time human motion evaluation optimization algorithm for tennis training robots. At the end of the paper, that is, the fourth part, through the way of field test and investigation, further proves the superiority of the improved real-time evaluation algorithm of human movement. The algorithm has good stability and accuracy and can meet the existing tennis training requirements. Show more

Keywords: Tennis training, artificial intelligence, intelligent robots, motion capture

DOI: 10.3233/JIFS-189444

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 6049-6057, 2021

Authors: Cheng, Yuan | Wang, Kunqian

Article Type: Research Article

Abstract: Small and medium-sized manufacturing enterprises have the characteristics of large numbers and small scales. Problems such as backward manufacturing technology, lack of talents, small amount of information resources, and insufficient product research and development capabilities have severely restricted the development of enterprises. The backward manufacturing design model cannot adapt to the development trend of modern manufacturing informatization. This paper proposes and designs a fuzzy inference model and fuzzy inference engine algorithm with threshold. In order to describe the numerical multiple input and multiple output variables in the industrial manufacturing design industry, the relevant experience is used to make numerical reasoning …decisions. Applying fuzzy sets and fuzzy theory to the expert system, a fuzzy rule model containing the membership function information and thresholds of the corresponding fuzzy sets is proposed and established, and a fuzzy reasoning system suitable for numerical and uncertain reasoning decisions is constructed. The improved grey relational analysis method is used to decompose and evaluate the exponential mathematical quantitative process of manufacturing enterprises. Based on the fuzzy Decision Analytic Network Process (DANP) method to calculate the relative weight of the influencing factors in the evaluation system, the evaluation index of the enterprise is obtained. Starting from the industrial manufacturing design process, this article constructs a relatively comprehensive and reasonable enterprise exponential mathematical quantitative process decomposition evaluation system. Considering that there are complex interactions between the various influencing factors in the system, the fuzzy Decision Making Trial and Evaluation Laboratory (DEMATEL) method is selected to process the direct impact matrix of the evaluation system, and the causal relationship between the indicators is obtained. The fuzzy exponential gray correlation method is used to evaluate the quantitative process of industrial manufacturing design, avoiding the shortcomings of traditional methods that only consider ideal values. Show more

Keywords: Industrial manufacturing design, quantitative process decomposition, DANP, fuzzy reasoning

DOI: 10.3233/JIFS-189445

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 6059-6068, 2021

Authors: Xie, Yun

Article Type: Research Article

Abstract: The urban rail transit power supply system is an important part of the urban power distribution network and the power source of the rail transit system. It is responsible for providing safe and reliable electrical energy to urban rail trains and power lighting equipment. This paper processes the obtained long-period rail transit power load learning sample data matrix, according to the principle of normalization processing, effectively eliminates irregular data in the sample set and fills in possible missing data, thereby eliminating bad data or fake data for model learning. Moreover, this avoids the generation of huge errors that cause exponential …growth in the model due to the increase in the learning sample size and the irregularity of the data. According to the characteristics of power load, this paper comprehensively considers the influence of temperature and date type on the maximum daily load, applies the fuzzy neural network model to the long-period load forecasting of long-period rail transit, and introduces the whole process of establishing the forecasting model in detail. Through detailed analysis of the actual data provided by the EUNITE network, the relevant factors affecting the daily maximum load were determined, and then the appropriate fuzzy input was selected to establish the corresponding fuzzy neural network prediction model, and a relatively ideal prediction result was obtained. The experimental results fully proved the great potential of fuzzy neural network in long-term power load forecasting. Show more

Keywords: Power load forecasting, fuzzy neural network, fuzzy logic, rail transit

DOI: 10.3233/JIFS-189446

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 6069-6079, 2021

Authors: Wang, Ruijuan | Zhuo, Wei

Article Type: Research Article

Abstract: The image intelligent processing analysis technology uses a computer to imitate and execute some intellectual functions of the human brain, and realizes an image processing system with artificial intelligence, that is, an image processing analysis technology is an understanding of an image. The degree of intelligent automated analysis and processing is low, many operations need to be done manually, causing human error, inaccurate detection, and time-consuming and laborious. Deep learning method can extract features step by step in the original image from the bottom to the top. Therefore, based on feature analysis technology, this paper uses the deep learning method …to intelligently and automatically analyse the visual image. This method only needs to send the image into the system, and then the manual analysis is not needed, and the analysis result of the final image can be obtained. The process is completely intelligent and automatically processed. First, improve the deep learning model and use massive image data to choose and optimize parameters. Results indicate that our method not only automatically derives the semantic information of the image, but also accurately understands the image accurately and improve the work efficiency. Show more

Keywords: Image intelligent, automatic processing analysis, deep learning

DOI: 10.3233/JIFS-189447

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 6081-6090, 2021

Authors: Liu, Chen | Sergeevna, Chernova Oksana

Article Type: Research Article

Abstract: With the development of science and technology, in the field of oilfield commissioning, the requirements for process management are more and more standardized and scientific, and the requirements for decentralized equipment status detection and maintenance are also higher and higher. It is the hope of any manager to eliminate hidden dangers and prevent them in a timely manner. This paper introduces an intelligent debugging model based on big data. Based on the big data mechanism, the model is divided into different functions according to different functions and requirements. It can ensure the authenticity of debugging data, coordinate all big data …work through the big data communication mechanism, and conduct scientific management of debugging data. The model is divided into three levels: data acquisition layer, data transmission layer and control management layer. The offshore oil intelligent debugging platform software based on big data technology is built. A new intelligent debugging method for offshore oil based on big data is presented to study the warning information, fault location and equipment health status of intelligent debugging. Development for Marine oil intelligent debugging applications, for business people to provide intelligent Marine oil intelligent debugging method, provide data support for management decision-making, implementation of the lean management data in the field of intelligent debugging, improving the capacity of intelligent debugging data analysis and mining, effective use of the existing intelligent debugging automation system and other related data in the system, solved the “huge amounts of data, information, the lack of a” awkward situation, improve intelligence debugging application function, meet the demand of intelligent debugging of each department, improve the efficiency of debugging and running reliability and intelligent management. Show more

Keywords: Intelligent debugging, offshore oil, big data, communication mechanism

DOI: 10.3233/JIFS-189448

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 6091-6101, 2021

Authors: Ruan, Kun | Li, Yuan

Article Type: Research Article

Abstract: Using the theoretical knowledge of ergonomics, physiology, and psychology, carried out the humanized design of human body adaptive sports equipment; using the theoretical knowledge of modeling, color, material science and other related disciplines, proposed the human body adaptive sports equipment Humanized design method. Aiming at the fuzziness of the industrial design of human adaptive sports equipment, fuzzy mathematics theory is used as an analysis tool, combined with the actual characteristics of the industrial design of human adaptive sports equipment, focusing on the nature of industrial design under fuzzy theory. Comprehensive analysis and understanding of design-related factors, and the introduction of …expert survey method in the case of no basic data source in innovative design, to obtain the weight value of single factor influence, this will help designers grasp the main contradiction, achieve a targeted, and Solve key problems with higher efficiency. Subsequent use of fuzzy mathematics tools to put forward a quantitative index for the selection of options, which will help analyze the pros and cons of the various options, so as to provide a reliable reference for decision makers. This method makes up for the shortcomings of traditional methods in the process of design factor analysis and program selection. Show more

Keywords: Human body adaptation, sports equipment, industrial design, fuzzy mathematics

DOI: 10.3233/JIFS-189449

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 6103-6112, 2021

Authors: Xu, Xia

Article Type: Research Article

Abstract: The current network environment is dynamic, open and extensible. In order to better ensure the needs of users, higher requirements are placed on link resource allocation. Based on the research and analysis of the instant communication protocol, this paper studies an intelligent routing evolution algorithm and related fault recovery strategy for the instant communication network. Research on instant messaging intelligent algorithms for routing evolution is mainly based on routing algorithms and artificial intelligence intelligent algorithms. When a link failure occurs in the communication network, the routing algorithm performs route reconstruction and optimization on the entire instant communication network. Considering that …there may be evolutionary needs of large-scale routing networks in practical applications, this paper introduces artificial intelligence intelligent algorithms to optimize intelligent algorithms to improve efficiency. A cognitive routing protocol based on MIMO (Multiple Input Multiple Output) technology is proposed. By using MIMO technology, a lot of gain is brought to the communication link under multiple antennas. These gains correspond to different link types. The protocol realizes cognition through intelligent routing evolution algorithm and predicts the state of the network. Setting the routing life and hello period according to the perceived network status can optimize the performance of the network. Show more

Keywords: Instant messaging, network link optimization, intelligent routing evolution algorithm, CRMA routing protocol

DOI: 10.3233/JIFS-189450

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 6113-6124, 2021

Authors: Sun, Tingting | Lv, Xingjun | Cai, Yakun | Pan, Yuqing | Huang, Jianchang

Article Type: Research Article

Abstract: The thesis starts with the connotation and attributes of software testing quality, introduces software testing quality evaluation methods, and analyzes and discusses software testing quality evaluation models based on fuzzy mathematics theory. Focusing on the key technical problems of software testing quality, discuss the key technologies to solve the software testing quality evaluation model establishment. Through the use of fuzzy models, the cost of software testing quality evaluation is effectively reduced, and the reliability of software testing quality evaluation methods is improved. This model can quickly evaluate the quality of software testing, can avoid the occurrence of local maxima, overcome …the shortcomings of existing evaluation models and tools, and can correctly reflect the relationship between the internal and external properties of the software. Using the new software testing quality evaluation method, comparing the evaluation models and tools used before, summarizing the methods of software testing quality improvement. The application of these methods effectively improves the software testing quality. Show more

Keywords: Fuzzy mathematics, fuzzy evaluation, software quality, test quality

DOI: 10.3233/JIFS-189451

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 6125-6135, 2021

Authors: Cao, Ning | Miao, Xiaoming | Zhang, Juan

Article Type: Research Article

Abstract: With the development of information technology and the reduction of storage equipment costs, a large number of databases have been able to create and store massive amounts of data. How to use this data to provide guidance and advice for business decisions is a difficult problem that decision analysis systems need to solve. This paper designs a new multi-dimensional heterogeneous network information model, defines the binary relational meta-path in the heterogeneous network and the n-ary relational meta-path, and studies the relationship of these meta-paths as a new way to guide network aggregation. An intelligent emergency decision support system based on …the GIS platform and the concept of the plan library was established. The system adopts the method of artificial intelligence and GIS technology to complete the management, analysis and processing of map space data, and realizes the rapid and automatic generation of emergency decision-making. Finally, through experiments on large-scale real and simulated data, it is verified that the system can effectively and efficiently analyze large-scale multi-dimensional heterogeneous networks. Show more

Keywords: Multidimensional network, heterogeneous information network, spatial intelligent decision system, rapid decision

DOI: 10.3233/JIFS-189452

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 6137-6149, 2021

Authors: Zheng, Yi

Article Type: Research Article

Abstract: In this paper, an in-depth analysis of automated production line faults based on fuzzy algorithms is carried out and based on an in-depth investigation of the mechanism of equipment faults, research work on equipment state prediction and production line fault diagnosis is carried out, and the corresponding algorithm model workflow is given, which has some practical application value for improving the accuracy of production line fault prediction. The algorithm with data mining association rules is proposed to extract the confidence parameters of the conditional state fuzzy net model, and an inverse conditional state fuzzy net is established based on the …conditional state fuzzy net for fault diagnosis and reasoning, and a dynamic confidence level reasoning mechanism is also established for reverse reasoning based on the iterative algorithm of maximum algebra. To monitor the operating status of the production line more intuitively, a production line fault prediction and analysis system is developed based on the platform, which mainly includes a data management module, state monitoring module, state prediction module, fault diagnosis module, and maintenance advice module, which can more easily realize the monitoring of the production line equipment state and fault early warning prompting, making the system more practical value. Show more

Keywords: Fuzzy algorithms, automation, production lines, failure analysis

DOI: 10.3233/JIFS-189453

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 6151-6162, 2021

Authors: Li, Qian | Li, Shuyuan

Article Type: Research Article

Abstract: Aiming at the precocious convergence, low search accuracy and easy divergence of most particle swarm optimizations with velocity terms, a particle swarm optimization (IWPSO) with random inertia weights and quantization is proposed. First, the inertia weights are obeyed to be distributed randomly, and the learning factors are adjusted asynchronously to optimize the parameters in BP network. Secondly, BP network is trained using the IWPSO algorithm based on the sample data. Finally, simulation experiments prove that the algorithm has significantly improved search speed, convergence accuracy, and stability compared with existing improved algorithms. Due to the characteristics of IWPSO algorithm, the BP …neural network optimized by IWPSO has better global convergence performance and is an efficient particle swarm optimization. Show more

Keywords: Optimization, artificial neural network, swarm intelligence algorithm

DOI: 10.3233/JIFS-189454

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 6163-6173, 2021

Authors: Fang, Zhichun | Zhu, Zhengguo | Chen, Xinyu

Article Type: Research Article

Abstract: The construction of tunnels is often long and deep buried tunnels, and the geological conditions are more complex. Based on Jianshan tunnel in Gansu Province, the special geological conditions such as high ground stress and weak interbedded surrounding rock make the excavation of tunnel easy to produce large deformation. In this article, the software finite difference software FLAC3D was used to establish numerical models and select the best construction method by comparing the deformation of the tunnel under different construction methods. Aiming at the deformation characteristics of soft rock tunnels in highland interbedded layers, the control measures of tunnel deformation …are discussed. Mainly consider the two aspects of the bolt support plan and the second lining construction time, comprehensively compare the deformation characteristics of the tunnel, and select the best working condition. The research results show that the combination of three-step temporary invert method and three-step ultra short bench method is recommended for the tunnel construction; when the bench length is 4 m, the deformation control effect of the tunnel is the best; by improving the length and angle of the anchor rod, the deformation of the tunnel can also be well controlled. Show more

Keywords: High ground stress, interbedded soft rock, construction technology, deformation control

DOI: 10.3233/JIFS-189455

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 6175-6183, 2021

Authors: Shao, Mengliang | Qi, Deyu | Xue, Huili

Article Type: Research Article

Abstract: Outlier detection is an important branch of data mining. This paper proposes an advanced fast density peak outlier detection algorithm based on the characteristics of big data. The algorithm is an outlier detection method based on the improved density peak clustering algorithm. This paper improves the original algorithm. From the perspective of outlier detection, although it is a clustering idea, it avoids the clustering process, reduces the time complexity of the cluster-based outlier detection algorithm, and absorbs. The outlier detection based on neighbors is not sensitive to data dimensions and other advantages. In the power industry, outlier detection can be …used in areas such as grid fault detection, equipment fault detection, and power abnormality detection. The simulation experiment of outlier detection based on the daily load curve of single and multiple transformers in a certain province shows that the improved algorithm can effectively detect outliers in the data. Show more

Keywords: Outlier detection, big data, KNN algorithm, density clustering

DOI: 10.3233/JIFS-189456

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 6185-6194, 2021

Authors: Yu, Hui | Hu, Lingyan

Article Type: Research Article

Abstract: Usually the highlights can be calculated with the specular term of the bidirectional reflectance distribution functions developed for glossy or matte materials. However, as for the translucent materials, complex appearance could be caused by the scattering of light inside the medium. An efficient highlight generation model is presented to simulate the highlight effects on smooth or rough surfaces or around the boundaries of objects made from translucent materials. The presented model is derived from the directional dipole model approximation of the diffusive part of the bidirectional scattering surface reflectance distribution function. Unlike the previous specular reflection models, the presented model …builds a relationship between the highlights and the scattered lights inside the medium by considering the refracted ray of the incident point and the ray toward the emergent point, which could represent the variation in fluence due to the internal scattering at the surface. By integrating a rendering process with the directional dipole model, the resulting highlight effects term could be represented in a similar way by the specular term of a bidirectional reflectance distribution function model. The number and the strength of the generated highlight pixels were compared among typical highlight generation models. It is demonstrated that the presented model could generate highlight effects at the appropriate positions and enhance the perceptual translucency of specific edge areas greatly. Show more

Keywords: Highlights, bidirectional scattering surface reflectance distribution function, bidirectional reflectance distribution function, directional dipole, subsurface scattering, translucency appearance

DOI: 10.3233/JIFS-189457

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 6195-6204, 2021

Authors: Li, Wenguang | Feng, Guosheng | Jia, Sumei

Article Type: Research Article

Abstract: This paper studies a hybrid power system composed of fuel cells, super capacitors and batteries. Super capacitors are used as auxiliary energy sources to provide the required high power when the car starts and accelerate, while absorbing braking energy when the car is braking. Fuzzy control is used to optimize its energy management strategy. The fuzzy controller of the three-energy source system takes the battery, super capacitor, and bus demand power as the input of the fuzzy controller, and the battery demand power and the fuel cell demand power as the fuzzy controller output. The system realizes the energy distribution …of super capacitors, fuel cells and storage batteries according to power requirements, thereby improving the performance of the system and extending the life of components. And with hydrogen consumption as the optimization goal, the particle swarm algorithm is used to optimize the parameters of the fuzzy membership function. Compared with the fuzzy control strategy without particle swarm optimization, the optimized fuzzy energy management strategy reduces the hydrogen consumption of fuel cell vehicles. 10 L/(100 km)-1, which improves the economy of the vehicle. Show more

Keywords: Fuel cell vehicles, hybrid powertrain, energy management strategy, fuzzy control, particle swarm optimization

DOI: 10.3233/JIFS-189458

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 6205-6217, 2021

Authors: Zhu, Yu | Liu, Xiantao

Article Type: Research Article

Abstract: In this paper, an in-depth study on the quantification of influencing factors and big data visualization of key monitoring indicators in the refined oil products market is carried out through fuzzy mathematical methods, and a system for quantifying influencing factors and big data visualization of key monitoring indicators in the refined oil products market with the fuzzy mathematical background is designed and implemented. The system realizes the functions of flow visualization, attack visualization, target tracking visualization, etc., and optimizes the system from the perspectives of performance and visualization effect. It achieves the display and interaction of multi-dimensional data in space …and time with multiple views, angles, and dimensions. Data tagging and data correlation for key aspects of the product production process are realized through fuzzy mathematics and other means, and a quality traceability system for the manufacturing industry is realized on this basis, through which the data of some key stages of the product production process can be displayed retrospectively. The study proves that the business model of refined oil logistics platform based on value network can significantly improve the user’s perceived value and benefit all parties within the value network, realizing the complementary advantages of refined oil production enterprises and logistics platform companies, improving the efficiency of enterprise’s logistics and maximizing the profit of each subject within the value network to achieve profitability for all parties. Show more

Keywords: Fuzzy mathematics, refined products market, quantification of influences, key monitoring indicators, big data visualization

DOI: 10.3233/JIFS-189459

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 6219-6229, 2021

Authors: Tian, Hui | Zhang, Zhujun | Yuan, Zhihua | Liu, Xiaochan | Qi, Yuyan | Wang, Zhenguo | Wang, Liang

Article Type: Research Article

Abstract: In view of the problems of low stiffness, small driving force and large balloon effect existing in the current soft actuator, this paper proposes an optimization method to enhance the overall stiffness of the soft gripper by using rigid components based on the multi-cavity soft pneumatic actuator. This paper introduces the main components of the actuator: the soft part poured by liquid silica gel, and the open rectangular rigid structures by 3D printed. The kinematics model of the finger is established based on the Piecewise Constant Curvature model(PCC). The bending performance of the enhanced stiffness gripper is verified by finite …element analysis(FEA): the tip force of actuator increased with the increase of the number of rigid structures when the bending angle is constant. According to the and experimental data, the overall stiffness of soft gripper is increased by the rigid structure without affecting the flexibility of operation. And the maximum weight which can grasp is 3.4 times that of the traditional soft gripper, improved the grasping range of the soft gripper effectively. Show more

Keywords: Soft gripper, stiffness-enhanced, PCC model, FEA

DOI: 10.3233/JIFS-189460

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 6231-6238, 2021

Authors: Wang, Yu | Lian, Zhengmei | Zou, Jihua

Article Type: Research Article

Abstract: The main reason that hinders early treatment of ACS patients is delayed patient decision-making (PD). In order to explore the delay factors of patients with ACS, this paper builds a machine learning-based analysis model of delay factors for patients with acute coronary syndrome based on machine learning. Moreover, this paper combines structural equations to analyze the factors affecting accidents, and uses the generalized ordered logit model in statistics and the popular random forest model in machine learning to establish the analysis models of the delay factors of acute coronary syndromes, and analyze the functional structure of the models. In addition, …this paper obtains data through actual survey methods, and analyzes the data through the model constructed in this paper to explore the risk factors that affect the delay in seeking medical treatment, which is presented through charts. The research results show that the model constructed in this paper is more reliable and can be applied in practice. Show more

Keywords: Machine learning, mountain area, acute coronary syndrome, delay in seeking medical treatment, factor analysis

DOI: 10.3233/JIFS-189461

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 6239-6250, 2021

Authors: Huang, Yan

Article Type: Research Article

Abstract: Enterprise marketing is affected by a variety of factors, which lead to certain fluctuations in corporate market influence, and it is difficult to effectively control the elasticity of market influence. In order to improve the elastic analysis effect of enterprise marketing investment, based on the machine learning algorithm, this paper uses the equilibrium movement model to construct an intelligent model suitable for marketing simulation analysis. The equilibrium movement model used in this paper is a simulation of a real situation, which can be used for predictive analysis and can measure how much an exogenous impact can cause endogenous variables to …change. Moreover, this paper establishes a mathematical model to express the influence of marketing with the help of producer surplus, quantify this influence, and use numbers to show the influence of marketing more intuitively. In addition, this paper uses case analysis to study the effect of model analysis. From the research process and conclusions, it can be seen that the model constructed in this paper has certain effects. Show more

Keywords: Balanced mobility model, marketing, investment, elasticity analysis

DOI: 10.3233/JIFS-189462

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 6251-6261, 2021

Authors: Zhu, Bin | Zhou, Jie

Article Type: Research Article

Abstract: In order to build a virtual urban planning model and improve the effect of urban planning, this paper builds a virtual urban planning design model based on GIS big data technology and machine learning algorithms, and proposes a solution that combines multiple features. With the development of polarized SAR in the direction of high resolution, a single feature often cannot fully express the detailed information of ground objects, resulting in poor classification results and low accuracy. The combination of multiple features can express feature information well. In addition, this paper uses the ELM method to plan SAR ground object classification, …uses an extreme learning machine classification algorithm with fast learning speed and good classification effect, and uses ELM as a classifier. Finally, this paper designs experiments to explore the performance of the model constructed in this paper from two aspects: detection accuracy and planning score. The research results show that the model constructed in this paper meets the expected goals. Show more

Keywords: GIS, big data, machine learning, urban planning

DOI: 10.3233/JIFS-189463

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 6263-6273, 2021

Authors: Jiang, Zhiqi | Wang, Xidong

Article Type: Research Article

Abstract: This paper conducts in-depth research and analysis on the commonly used models in the simulation process of air pollutant diffusion. Combining with the actual needs of air pollution, this paper builds an air pollution system model based on neural network based on neural network algorithm, and proposes an image classification method based on deep learning and Gaussian aggregation coding. Moreover, this paper proposes a Gaussian aggregation coding layer to encode image features extracted by deep convolutional neural networks. Learn a fixed-size dictionary to represent the features of the image for final classification. In addition, this paper constructs an air pollution …monitoring system based on the actual needs of the air system. Finally, this article designs a controlled experiment to verify the model proposed in this article, uses mathematical statistics to process data, and scientifically analyze the statistical results. The research results show that the model constructed in this paper has a certain effect. Show more

Keywords: Neural network, machine learning, air pollution, intelligent monitoring

DOI: 10.3233/JIFS-189464

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 6275-6285, 2021

Authors: Xiaohui, Chen | Xi, Yang | Haoyuan, Pang | Yongjian, Ou

Article Type: Research Article

Abstract: This article discusses the design and implementation of a 100 G tunable laser optical module, and briefly introduces the functions of each module in the MCU. The main technologies involve TEC control, wavelength locking, wavelength tuning, and power compensation. By analyzing the traditional positional proportional integral and differential algorithm, improving the proportional integral and differential algorithm, and using the algorithm to achieve wavelength locking, this can prevent the wavelength drift or even the lock due to the overload of the adjustment during the system adjustment process.

Keywords: PID, wavelength locking, tunable laser, TEC

DOI: 10.3233/JIFS-189465

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 6287-6294, 2021

Authors: Chen, Yuan

Article Type: Research Article

Abstract: The macro traffic flow model of expressway is transformed into a general discrete-time nonlinear system model including this model by using the repeatability of the macro traffic flow model, and then a parameter identification algorithm based on iterative learning is designed for this general discrete-time nonlinear system model. The convergence of this parameter identification scheme is proved by strict theoretical derivation and robustness. Simulation results verify the effectiveness of the algorithm.

Keywords: Macro traffic flow model, iterative learning control, parameter identification

DOI: 10.3233/JIFS-189466

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 6295-6303, 2021

Authors: Xiong, Cheng | Li, You | Long, Nuoya

Article Type: Research Article

Abstract: Based on the introduction of the principle of the optical wireless system, the WDM-ROF based on hybrid modulation of MZM and OFM is designed WDM-ROF-PON system architecture, using simulation software to build the system to verify the rationality of the MZM and OFM hybrid modulation system structure; and put forward an MZM and OFM hybrid modulation scheme, using IRZ code in the downlink data stream, with better extinction ratio and dispersion tolerance, reducing the cost of the user receiving equipment, improving the system transmission quality. The simulation results show that the scheme of MZM and OFM hybrid modulation WDM-of-pon network …architecture is reasonable and practical. Show more

Keywords: MZM and OFM hybrid modulation, WDM-PON, ROF

DOI: 10.3233/JIFS-189467

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 6305-6313, 2021

Authors: Ma, Xiaona

Article Type: Research Article

Abstract: English text is difficult to recognize under the interference of blurred background, so it is necessary to improve the fixed-point tracking technology of English text. Based on machine learning algorithms, this paper studies the fixed-point tracking model of English reading text based on mean shift and multi-feature fusion. The target tracking algorithm based on mean shift obtains the description of the target model and the candidate model by calculating the pixel feature probability in the target area and the candidate area. Then, it uses the similarity function to measure the similarity between the initial frame target model and the current …candidate model, selects the candidate model that maximizes the similarity function, and obtains the target model mean offset vector. Finally, it continuously iteratively calculates the offset vector based on this vector, and finally converges to the true position of the target, thereby achieving the effect of tracking. In general, it is verified that the model constructed in this paper works well through control experiments. Show more

Keywords: Machine learning, mean shift, multi-feature fusion, English reading, fixed-point tracking

DOI: 10.3233/JIFS-189468

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 6315-6325, 2021

Authors: Song, Xin

Article Type: Research Article

Abstract: The difficulty of obtaining the characteristics of the corpus database of neural machine translation is a factor hindering its development. In order to improve the effect of English intelligent translation, based on the machine learning algorithm, this paper improves the multi-objective optimization algorithm to construct a model based on the English intelligent translation system. Moreover, this paper uses parallel corpus and monolingual corpus for model training and uses semi-supervised neural machine translation method to analyze the data processing path in detail and focuses on the analysis of node distribution and data processing flow. In addition, this paper introduces data-related regularization …items through the probabilistic nature of the neural machine translation model and applies it to the monolingual corpus to help the training of the neural machine translation model. Finally, this paper designs experiments to verify the performance of this model. The research results show that the translation model constructed in this paper is highly intelligent and can meet actual translation needs. Show more

Keywords: Improved algorithm, machine learning, multi-objective optimization algorithm, English translation

DOI: 10.3233/JIFS-189469

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 6327-6337, 2021

Authors: Zhao, Chao | Yang, Hongling | Li, Xiaoqian | Li, Rui | Zheng, Shoucun

Article Type: Research Article

Abstract: The intelligent scheduling algorithm for hierarchical data migration is a key issue in data management. Mass media content platforms and the discovery of content object usage patterns is the basic schedule of data migration. We add QPop, the dimensionality reduction result of media content usage logs, as content objects for discovering usage patterns. On this basis, a clustering algorithm QPop is proposed to increase the time segmentation, thereby improving the mining performance. We hired the standard C-means algorithm as the clustering core and used segmentation to conduct an experimental mining process to collect the ted QPop increments in practical applications. …The results show that the improved algorithm has good robustness in cluster cohesion and other indicators, slightly better than the basic model. Show more

Keywords: Fuzzy clustering algorithm, membership, martial arts video, image segmentation, intersection clustering, object extraction

DOI: 10.3233/JIFS-189470

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 6339-6347, 2021

Article Type: Other

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 6349-6349, 2021

Authors: Ramachandran, Varatharajan

Article Type: Editorial

Abstract: This special issue of the Journal of Intelligent & Fuzzy Systems contains selected articles of Fuzzy model for human autonomous computing in extreme surveillance and it’s applications

DOI: 10.3233/JIFS-189475

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 6351-6353, 2021

Authors: Lalitha, S.

Article Type: Research Article

Abstract: Cancer has been one of the most serious health challenges to the human kind for a long period of time. Lung cancer is the most prevalent type of cancer which shows higher death rates. However, lung cancer mortality rates can be tracked by periodic screening. With the advanced medical science, the society has reaped numerous benefits with respect to screening equipments. Computed Tomography (CT) is one of the popular imaging techniques and this work utilizes the CT images for lung cancer detection. An early detection of lung cancer could prolong the lifetime of the patient and is made effortless by …the latest screening technology. Additionally, the accuracy of disease detection can be enhanced with the help of the automated systems, which could support the healthcare experts in effective diagnosis. This article presents an automated lung cancer detection system equipped with machine learning algorithm, which can differentiate between the benign, malignant and normal classes of lung cancer. The accuracy of the proposed lung cancer detection method is around 98.7%, which is superior to the compared approaches. Show more

Keywords: Cancer, Lung cancer detection, CT images, machine learning

DOI: 10.3233/JIFS-189476

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 6355-6364, 2021

Authors: Poonguzhali, S, | Chakravarthi, Rekha

Article Type: Research Article

Abstract: Diabetes is one of the chronic metabolic disorder. Under diabetic condition, blood glucose level should be properly maintained in order to avoid various major diseases. The condition will be worse when it is not controlled at an earlier stage. Even massive heart attack cannot be identified when the patient has been affected by diabetes. Early diagnosis is required for preventing fatal diseases like cardiac problem, asthma, heart attack etc. In the proposed system measurement of glucose level and Prediction/ diagnosis of diabetes is based on the real time low complexity neural network implemented on a wearable device. A larger network …is required for the diagnosis which needs to be present far-off in cloud and initiated for diagnosis and classification process of diabetes whenever it is essential. People can be able to manage and monitor the required basic parameters like heart rate, glucose level, lung condition, pressure of blood using the corresponding light weight biosensors in the wearable device designed through telemedicine technology. The quality of the disease diagnosis and Prediction is improved in this way. Using neural network feed forward prediction model in conjugation with back propagation algorithm and given training data, the system predicts whether the patient is prone to diabetes or not. The proposed work was evaluated using physic sensor data from physio net data base and also tested for real time functioning. The Proposed system found to be efficient in accuracy, sensitivity and fast operative. Show more

Keywords: Continuous glucose monitoring, diabetic condition prediction, early medical diagnosis, ANN, remote health assistance

DOI: 10.3233/JIFS-189477

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 6365-6374, 2021

Authors: Ajitha, P. | Sivasangari, A. | Immanuel Rajkumar, R. | Poonguzhali, S.

Article Type: Research Article

Abstract: Text Sentiment Analysis is a system where text feeling polarity is positive or negative or neutral from a series of texts or documents or public opinions on a particular product or general subject. Using machine learning and natural language processing techniques, the current work aims to gain insight into sentiment mining on tweets. Text classification is accomplished using Machine Learning Algorithm-based fusion technique. This research suggested a system for grading feelings based on a lexicon. Bag-of-words (BOW) or lexicon-based methodology is currently the main standard way of modeling text for machine learning in sentiment analysis approaches. Marketers can use sentiment …analysis to analyze their business and services, public opinion, or to evaluate customer satisfaction. Organizations can even use this analysis to gather significant feedback on issues related to newly released products. The main objective of this is to resolve the data overload problem. Show more

Keywords: Sentiment analysis, natural language processing, lexicon method, naive bayesian algorithm

DOI: 10.3233/JIFS-189478

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 6375-6383, 2021

Authors: Ma, Hongjiang | Luo, Xu

Article Type: Research Article

Abstract: The irrationality between the procurement and distribution of the logistics system increases unnecessary circulation links and greatly reduces logistics efficiency, which not only causes a waste of transportation resources, but also increases logistics costs. In order to improve the operation efficiency of the logistics system, based on the improved neural network algorithm, this paper combines the logistic regression algorithm to construct a logistics demand forecasting model based on the improved neural network algorithm. Moreover, according to the characteristics of the complexity of the data in the data mining task itself, this article optimizes the ladder network structure, and combines its …supervisory decision-making part with the shallow network to make the model more suitable for logistics demand forecasting. In addition, this paper analyzes the performance of the model based on examples and uses the grey relational analysis method to give the degree of correlation between each influencing factor and logistics demand. The research results show that the model constructed in this paper is reasonable and can be analyzed from a practical perspective. Show more

Keywords: Neural network, improved algorithm, logistics demand, forecasting model

DOI: 10.3233/JIFS-189479

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 6385-6395, 2021

Authors: Xie, Ying

Article Type: Research Article

Abstract: From the beginning to the end, monetary policy has focused too much on the control of the supply side. At present, the single supply-based monetary policy is ineffective. Therefore, it is urgent to change the current single direct supply-side regulation and control policy and replace it with a non-single and indirect control policy that combines supply and demand. Based on machine learning algorithms, this paper constructs a monetary policy analysis model based on dynamic stochastic general equilibrium methods to analyze the interactive effects of monetary policy and other policies. Moreover, this paper uses the dynamic stochastic general equilibrium model to …simulate and analyze the economic effects of fiscal policy. In addition, this paper compares the economic effects of monetary policy and other policies and conducts verification and analysis through actual data. The obtained results show that the model constructed in this paper achieves the expected effect. Show more

Keywords: Dynamic stochastic, general equilibrium model, monetary policy, policy effect

DOI: 10.3233/JIFS-189480

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 6397-6408, 2021

Authors: Wang, Linuo

Article Type: Research Article

Abstract: Injuries and hidden dangers in training have a greater impact on athletes ’careers. In particular, the brain function that controls the motor function area has a greater impact on the athlete ’s competitive ability. Based on this, it is necessary to adopt scientific methods to recognize brain functions. In this paper, we study the structure of motor brain-computer and improve it based on traditional methods. Moreover, supported by machine learning and SVM technology, this study uses a DSP filter to convert the preprocessed EEG signal X into a time series, and adjusts the distance between the time series to classify …the data. In order to solve the inconsistency of DSP algorithms, a multi-layer joint learning framework based on logistic regression model is proposed, and a brain-machine interface system of sports based on machine learning and SVM is constructed. In addition, this study designed a control experiment to improve the performance of the method proposed by this study. The research results show that the method in this paper has a certain practical effect and can be applied to sports. Show more

Keywords: Machine learning, SVM, sports, brain-computer interface

DOI: 10.3233/JIFS-189481

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 6409-6420, 2021

Authors: Hongjin, Sun

Article Type: Research Article

Abstract: The financial supply chain is affected by many factors, so an artificial intelligence model is needed to identify supply chain risk factors. This article combines the actual situation of the financial supply chain, improves the traditional machine learning algorithm, and takes the actual company as an example to build a corresponding risk factor recognition model. From the perspective of optimizing the supply chain financial model, this paper combines the functions of the Internet of Things technology and the characteristics of the supply chain financial inventory pledge financing model to design a new type of inventory pledge financing model. The new …model makes up for the defects of the original model through the functions of intelligent identification, visual tracking and cloud computing big data processing of the Internet of Things technology. In addition, this study verifies the performance of the system, uses a large amount of data in Internet finance as an object, and obtains the corresponding results through mathematical statistical analysis. The research results show that the model proposed in this paper has a certain effect on the identification and analysis of financial supply chain risk factors. Show more

Keywords: Machine learning, finance risk, supply chain, risk factors

DOI: 10.3233/JIFS-189482

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 6421-6431, 2021

Authors: Li, Zhou

Article Type: Research Article

Abstract: The accurate mastery of demand information enables retailers to better respond to consumers and effectively manage inventory. However, the precise connection and interaction between this information collection and inventory management is more difficult to measure. In view of this, this paper proposes a research on inventory model based on consumer web search. Moreover, centering on the two main actors in the online search environment, consumers and retailers, this paper fully considers their characteristics and situations to construct an inventory model in the online search environment, and analyzes the ordering strategy. Moreover, based on the digital traces left by consumers in …the decision-making process, this paper uses general search indicators and specific search indicators to measure consumer web search to explore the relationship between consumer web search indicators and the demand conversion rate proposed in the model. Moreover, this paper analyzes the model with examples. The research results are in line with model construction expectations. Show more

Keywords: Machine learning, consumer, behavior analysis, improvement model

DOI: 10.3233/JIFS-189483

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 6433-6443, 2021

Authors: Yan, Tang | Pengfei, Li

Article Type: Research Article

Abstract: In marketing, problems such as the increase in customer data, the increase in the difficulty of data extraction and access, the lack of reliability and accuracy of data analysis, the slow efficiency of data processing, and the inability to effectively transform massive amounts of data into valuable information have become increasingly prominent. In order to study the effect of customer response, based on machine learning algorithms, this paper constructs a marketing customer response scoring model based on machine learning data analysis. In the context of supplier customer relationship management, this article analyzes the supplier’s precision marketing status and existing problems …and uses its own development and management characteristics to improve marketing strategies. Moreover, this article uses a combination of database and statistical modeling and analysis to try to establish a customer response scoring model suitable for supplier precision marketing. In addition, this article conducts research and analysis with examples. From the research results, it can be seen that the performance of the model constructed in this article is good. Show more

Keywords: Machine learning, data analysis, marketing, customer response, scoring model

DOI: 10.3233/JIFS-189484

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 6445-6455, 2021

Authors: Han, Ying

Article Type: Research Article

Abstract: When choosing stock investment, there are many stock companies, and the stock varieties are also complicated. At present, there are various systems for evaluating stock performance in the market, but there is no uniform standard, so investors often cannot effectively invest in stocks. Simultaneously, stock management companies also have their own characteristics, and there are differences in shareholding structure and internal management structure. Based on this, based on multiple regression models and artificial intelligence models, this paper constructs a stock return influencing factor analysis model to statistically describe the sample data and factor data, and tests the applicability of the …five-factor model for performance evaluation of mixed stocks. In addition, this article combines the actual situation to carry out data simulation analysis and uses a five-factor analysis model to carry out quantitative research on stock returns. Through data simulation analysis, we can see that the model constructed in this paper has a certain effect in the analysis of factors affecting stock returns. Show more

Keywords: Multiple regression, artificial intelligence, stock returns, influencing factors

DOI: 10.3233/JIFS-189485

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 6457-6467, 2021

Authors: Yaxu, Yang

Article Type: Research Article

Abstract: The loose logistics market, the weak value-added service capabilities of enterprises, and the backward construction and operation of logistics networks have led to high logistics costs and low efficiency in some enterprises. In order to improve the comprehensive evaluation effect of enterprise logistics enterprise competitiveness, this paper builds a comprehensive evaluation model of logistics enterprise competitiveness based on SEM model based on machine learning technology. Moreover, in order to more accurately grasp the law of customer logistics mode selection behavior, this paper adds the adaptive value of the latent variables of the logistics mode service characteristics obtained through the SEM …model to the utility function of the logistics mode to obtain the SEM-NL integrated model. In addition, starting from the analysis of the key factors affecting the competitiveness of enterprise logistics, this paper constructs an evaluation model of enterprise logistics competitiveness, and analyzes and studies the comprehensive competitiveness of enterprise logistics through two aspects of logistics actual competitiveness and logistics future development potential. The research results show that the model constructed in this paper is suitable for the comprehensive evaluation of the competitiveness of logistics enterprises. Show more

Keywords: SEM model, logistics enterprise, competitiveness, comprehensive evaluation

DOI: 10.3233/JIFS-189486

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 6469-6479, 2021