Journal of Computational Methods in Sciences and Engineering - Volume 22, issue 6

Authors: Li, Qian

Article Type: Research Article

Abstract: The abnormality of communication link of mobile Internet of Things will threaten the security of communication of mobile Internet of Things, and the existing abnormality detection method is limited due to low accuracy, long time consumption and high energy consumption. To this end, the anomaly detection method of communication link of mobile Internet of Things based on EM algorithm is proposed in this study. Firstly, the anomaly range of the Internet of Things is located according to the communication node information of the data changes. Then the abnormal link of the target is judged and the anomaly feature of the …communication link of the Internet of Things based on twin neural network is extracted. Finally, EM algorithm is improved with semi-supervised machine learning method to detect abnormal communication links of mobile Internet of Things. The experimental results show that the proposed method has the advantages of high precision, short time consumption and low energy consumption in the anomaly detection of communication links in the Internet of Things. Show more

Keywords: EM algorithm, mobile internet of Things, communication link, anomaly feature extraction, anomaly detection

DOI: 10.3233/JCM-226416

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 22, no. 6, pp. 1967-1979, 2022

Authors: Chen, Zhitao | Yang, Xiaodong | Jin, Bo | Guo, Mingya | Li, Miaomiao

Article Type: Research Article

Abstract: In the process of industrial Internet security situation analysis, affected by the perception model, the average approximation error of security assessment results is high. Therefore, an industrial Internet security evaluation technology based on digital twin is proposed. Design the industrial Internet assessment mode, design the industrial Internet technical framework according to the digital twin, and clarify the elements of security situation assessment. According to the sliding time window, the fuzzy knowledge base is established. The security situation awareness model is designed based on digital twin, combined with the calculation results of fuzzy closeness to improve the accuracy of automatic perception …results. Establish a multi port access protocol and realize the industrial Internet security evaluation technology under the digital twin with the help of the backed up coded key file. The experimental results show that the accuracy of the evaluation results of the design method is always above 95%, the tamper-proof success rate is always above 95%, and the physical value difference between the final values is 0.10. Therefore, this method effectively improves the evaluation accuracy. and tamper-proof success rate, reducing the difference value, it effectively controls the deviation of Internet operation data, provides security, is feasible and effective. Show more

Keywords: Digital twins, industrial internet, safety assessment technology, security situational awareness model, fuzzy knowledge base, access protocol, encryption key

DOI: 10.3233/JCM-226375

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 22, no. 6, pp. 1981-1994, 2022

Authors: Zhong, Zufeng

Article Type: Research Article

Abstract: Emergency materials transportation, both economic and societal, is one of the most important parts of unconventional emergency management. In the present study, we built a quantitative simulation model underlying the mechanism of emergency materials transportation specifically regarding typhoon disasters. We then explored the internal influence factors and association mechanisms of the dynamic model as they relate to the effective control and guidance of emergency materials transportation. Using system dynamic model, this paper conducts the simulation study to identify the key influencing factors for the speed of emergency materials transportation. The relationships between influencing factors and the emergency capability were analyzed …qualitatively. On this basis, SD flow chart was built. A typhoon disaster event in Leizhou Peninsula, China, is used as an example to validate the effectiveness and feasibility of the proposed model, as well as to simulate different emergency management strategies. Results of governmental emergency materials transportation are key factors in process of emergency formulating the policy to improve the speed and efficiency for emergency materials transportation during the emergency management process. Show more

Keywords: Typhoon disaster, emergency materials transportation, system dynamics, simulation, China

DOI: 10.3233/JCM-226377

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 22, no. 6, pp. 1995-2006, 2022

Authors: Yuan, Jianlin

Article Type: Research Article

Abstract: In 2020, COVID-19 dragged down the economic development of various countries and the real estate industry was seriously affected. According to the meaning construction theory (SMT), this paper selects the real estate risk indicators to accurately measure the risk of Liaoning real estate. Based on the factor analysis method, the weight of real estate risk index in Liaoning province is calculated, which provides the basis for the further development of real estate risk in Liaoning province. According to the theory of spatial statistics, the real estate risk model of Liaoning province is constructed, and the real estate risk analysis of …Liaoning province is completed. In order to accurately measure the effect of real estate risk spatial model in Liaoning province, the least square regression, spatial error regression, spatial error regression (FSEM) and spatial lag regression (FSLM) are compared. The regression effect of spatial lag regression model is the best. According to the results of the spatial model of real estate in Liaoning province, the spatial distribution of real estate in different cities in Liaoning province has a certain correlation, but the degree of connection is low. By using the spatial risk model of real estate in Liaoning province, the risk value of real estate in 2019 is low. Show more

Keywords: Factor analysis, spatial statistics, real estate risk, combination method

DOI: 10.3233/JCM-226379

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 22, no. 6, pp. 2007-2021, 2022

Authors: Zhao, Jie

Article Type: Research Article

Abstract: Due to the problems of high false positive rate and low abnormal detection rate in the current IoT node access security control method, based on this, this paper designs a new IoT node access security control method. Firstly, the information security sharing structure is designed, the data collection work is completed, and the data is preprocessed. The preprocessed data is then shared and backed up through blockchain technology. Finally, take the login time, number of logins, login time, number of query results, query time and number of queries as the access constraints, and complete the security control of the access …to the IoT nodes by correctly setting the access authorization conditions. The experimental results show that the false positive rate of IoT access behavior detection is always lower than 0.3%, the detection rate of IoT access anomaly is low, the detection sensitivity is higher than 80%, and the node encryption complexity is low, which has certain application value. Show more

Keywords: Blockchain technology, internet of things node access, safety control, access authorization conditions

DOI: 10.3233/JCM-226381

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 22, no. 6, pp. 2023-2036, 2022

Authors: Ren, Shanchang | Qie, Yushi | Xie, Zhicheng

Article Type: Research Article

Abstract: In order to improve the analysis effect of tennis automatic transmitter path, this study designed a tennis automatic transmitter path analysis method based on artificial intelligence technology. Firstly, the structure of tennis automatic transmitter is designed, including five parts: ball receiving structure, ball sending structure, ball storage structure, launching structure and moving structure. Then, a grid model of the path distribution after the tennis ball is launched is constructed, and the constraint parameters of the path planning of the launcher are optimized. Finally, the force and running track of the tennis ball before and after launching are analyzed to realize …the automatic launching path analysis of the tennis ball. The experimental results show that the convergence value of this method is 1.39%, and it only takes 3.5 minutes to generate the path analysis results. Therefore, this method has good application effect in terms of convergence and timeliness, and can be effectively applied to the path analysis of tennis automatic transmitter. Show more

Keywords: Artificial intelligence technology, simulation method, tennis, automatic transmitter, path analysis

DOI: 10.3233/JCM-226386

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 22, no. 6, pp. 2037-2050, 2022

Authors: Xie, Zhicheng | Ren, Shanchang | Qie, Yushi

Article Type: Research Article

Abstract: In order to solve the problems of low recognition efficiency, low recognition rate and large recognition error of traditional methods, an application method of artificial intelligence technology in athletes’ running foul recognition was proposed. Build the image acquisition model of sports athletes’ running foul, divide each frame of the image samples into static area and motion area, and get the motion direction estimation results; K-means in the field of artificial intelligence is used to cluster the characteristics of sports athletes’ rush foul action, and LLE algorithm is used to reduce the dimension of features; The background subtraction method is used …to detect the foul target of rush, and the Bayesian algorithm is used to construct the recognition model of sports athletes’ foul of rush, which is used to identify the foul target. The experimental results show that the recognition rate of this method has reached more than 72%, and continues to increase, and the recognition error is only 2%, which effectively improves the recognition rate and reduces the recognition error, which is feasible and effective. Show more

Keywords: Artificial intelligence, foul identification, K-means clustering, feature dimensionality reduction, LLE algorithm, background subtraction, static area, dynamic area

DOI: 10.3233/JCM-226388

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 22, no. 6, pp. 2051-2063, 2022

Authors: Lv, Yongfei | Li, Mingcheng | Li, Bin

Article Type: Research Article

Abstract: With the arrival of sports wave, it is increasingly important to measure the posture of human body in movement. Aiming at the problems of low measurement accuracy and long measurement time in the traditional sports posture measurement algorithm, a sports posture measurement algorithm based on multi-sensor combination is proposed. The acceleration sensor, gyroscope and magnetoresistive sensor are combined to collect the sports posture data. The sliding mean filtering method and Z-score standardization method are used to reduce the noise and standardize the collected data. Based on the data processing results, the sports state is divided according to the dispersion characteristics, …and the posture of any joint node is judged. According to the judgment results, the sports posture is measured. The simulation results show that the proposed method has less error, higher measurement accuracy and shorter measurement time. It can provide theoretical support for the practical application of motion attitude measurement. Show more

Keywords: Multisensor joint, athletic sports, attitude measurement, acceleration sensor, gyroscope, magnetoresistive sensor, moving mean filtering

DOI: 10.3233/JCM-226393

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 22, no. 6, pp. 2065-2076, 2022

Authors: Zhou, Liping

Article Type: Research Article

Abstract: Traditional motion posture monitoring system has some problems such as time-consuming monitoring, low monitoring accuracy and poor monitoring effect. Therefore, this paper designs a real-time motion posture monitoring system based on sensor data flow. In the aspect of hardware, the whole structure of human motion posture monitoring system is designed. The mPU-92/65 six-axis motion processing sensor is selected to collect motion posture, and the module of human motion status detection is designed by MEMS sensor. In software, according to the amplitude fusion information of sensor output and correlation mining, fuzzy fusion model of motion posture data acquisition is established by …using correlation component detection method, and real-time monitoring of motion posture is realized by combining sensor data flow technology. The experimental results show that when the number of iterations is 300, the motion posture monitoring accuracy of the designed system can reach 99.57%, the motion posture monitoring time is only 31 ms, and the motion posture monitoring recall rate is as high as 98.65%, indicating that the designed system can improve the motion posture monitoring effect. Show more

Keywords: MEMS sensor, sensor data flow, detection of relevant components, motion posture, association mining

DOI: 10.3233/JCM226400

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 22, no. 6, pp. 2077-2091, 2022

Authors: Zhang, Yang

Article Type: Research Article

Abstract: Because the formation path information is not extracted in the process of robot formation motion path cooperative control, the image processing time is long and the effect of avoiding obstacles to reach the target position is poor. Therefore, a robot formation motion path cooperative control method based on machine vision is proposed. Through the design of embedded chip control module, image acquisition module and communication module, the application process of machine vision technology is designed, and the target features in the motion path of robot formation are extracted, including other robot targets and obstacle targets in the formation. Then, the …formation path information is extracted based on image preprocessing. On this basis, using the formation form of virtual structure-driver following method, the obstacle avoidance control of robot formation motion path is completed by potential field method. The experimental results show that after using this method, the images of its CCD camera when performing various processing are less than 200 ms. The moving environment image shows that this method has high processing performance for robot formation, and under the control of this method, the formation can change the formation and intelligent robot to avoid obstacles and reach the target position. Show more

Keywords: Robot formation, machine vision, moving path, formation change, obstacle avoidance control, CCD camera, virtual pilot-following method

DOI: 10.3233/JCM-226404

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 22, no. 6, pp. 2093-2105, 2022

Authors: Zhang, Ying | Luo, Xiaobo

Article Type: Research Article

Abstract: In order to improve the recall and precision of image retrieval, a visual retrieval method of digital media image features based on active noise is proposed. In this paper, Canny algorithm is used to detect the edge of the image to get the feature information of the edge of the image. The RGB color space model is used to decompose the color information of the image, and the color characteristic information of the image is obtained. Extracting image features to retain the useful information contained in the image as much as possible; In order to facilitate the visual retrieval of …image features, reduce the retrieval complexity and further fuse image features, FPCA and ReliefF algorithms are used to reduce the dimensionality of image features, and the active noise control method is used to sharpen the image. After processing the results, a digital media image feature visual retrieval platform is established to realize the visual retrieval of digital media image features. Experimental results show that the proposed method has a high accuracy of over 80% and a high recall rate of 95.2%. Show more

Keywords: Active noise control, image features, visual retrieval, canny algorithm, wavelet PCA, ReliefF algorithm

DOI: 10.3233/JCM-226407

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 22, no. 6, pp. 2107-2120, 2022

Authors: Zhang, Yu

Article Type: Research Article

Abstract: To solve the problem of missing or distorted detail texture when manually adjusting image parameters, a weak illumination image enhancement algorithm based on cyclic generation game network is proposed. The image features are normalized by Gaussian distribution. Combined with homomorphic filtering theory and defogging operation, the image is generated and denoised according to the network brightness to enhance the weak illumination image. The experimental results show that after using this method to process the image, the image entropy increases by 6.8%, the contrast increases by 27.5%, and the noise content decreases by 24.1%. It has better contrast. It can not …only meet the enhancement effect of weak light, but also ensure the details of the image, so that the image has richer details and good visual appearance. Show more

Keywords: Cyclic generation countermeasure network, weak illumination image, enhancement algorithm, normalization treatment, brightness sensitivity

DOI: 10.3233/JCM-226410

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 22, no. 6, pp. 2121-2133, 2022

Authors: Wang, Yuanyuan

Article Type: Research Article

Abstract: In order to improve the accuracy, efficiency and network throughput of multi-channel weak signal synchronous acquisition in the network, a multi-channel weak signal synchronous acquisition method in remote communication network is designed. Firstly, by analyzing the multi-channel structure of remote communication network, the interference factors of multi-channel weak signal acquisition are determined. The parameter model method is used to estimate the bispectrum of weak signals, complete the multi-channel weak signal extraction of remote communication network, and preprocess the multi-channel weak signals of remote communication network by average filtering method. On this basis, the characteristics of multi-channel weak signals in the …remote communication network are judged, and their characteristics are changed through the short time window function in the time domain, and the multi-channel weak signal synchronous catcher in the remote communication network is constructed to realize the synchronous acquisition of multi-channel weak signals in the remote communication network. The experimental results show that this method has high accuracy, short time-consuming and good network throughput. The acquisition accuracy of this method is always maintained at more than 90%. Show more

Keywords: Long distance communication network, multi channel weak signal, synchronous capture, parametric model, short time window function in time domain

DOI: 10.3233/JCM-226397

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 22, no. 6, pp. 2135-2148, 2022

Authors: Qi, Wei | Liu, Zihan | Xu, Yiting | Wang, Jiawei

Article Type: Research Article

Abstract: For moving object detection and trajectory prediction in video images, it is necessary to perform image processing, feature extraction, and localization of the object. Therefore, this paper designs an optimized Kalman-Elman (KE) algorithm for trajectory prediction. In order to remove the noise points on the measured values in the Kalman filter algorithm and to solve the problem of the random setting of the initial weights and thresholds of the Elman neural network, we encode the above parameters and improve the two algorithms by using Particle Swarm Optimization (PSO). Quantitative values of the object feature extraction are used as input parameters …of the Elman neural network. After a large amount of training, we obtain the predicted position of the moving object finally. The experimental results show that the prediction error of this method is significantly smaller when it is compared with previous methods. Show more

Keywords: Image processing, feature extraction, trajectory prediction, Particle Swarm Optimization

DOI: 10.3233/JCM-226342

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 22, no. 6, pp. 2149-2159, 2022

Authors: Zhang, Jinyan

Article Type: Research Article

Abstract: This paper studies how a couple in a family can reasonably allocate the family wealth to investment, consumption and life insurance in terms of of partial information, so as to maximize the family wealth. After constructing an appropriate mathematical model, the optimal strategy is mainly discussed before and after the death of the first family member, the corresponding value function is obtained, as well as the explicit solution of optimal strategy under the logarithmic utility function is given.

Keywords: Investment-consumption-life insurance, optimal strategy, partial information, HJB equation, logarithmic utility function

DOI: 10.3233/JCM-226344

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 22, no. 6, pp. 2161-2172, 2022

Authors: Yu, Jian | Xiong, Zenggang | Bao, Qi | Ning, Xiao

Article Type: Research Article

Abstract: At present, college students generally choose courses according to their own interests or understanding of the course, which has a certain subjectivity and blindness. In many cases, students know little about the courses before class, and only rely on the course name to guess the course content, so as to decide whether to take this course. However, the existing studies are mainly aiming at online learning resources which are heterogeneous, these methods cannot be effectively applied to the recommendation of university courses. This paper explores improve collaborative filtering for university application environments, provides a knowledge recommendation algorithm for university elective …courses. First, we created individual models of the course and the students based on background information. Next, we use context-based recommendation and “Parent Class Filling” method to reduce the impact of Cold Start and Sparsity problem on the initial stage of the system. Then, recommendations are generated based on the course evaluation model and similarity matrix. We select several commonly used algorithms to achieve the recommendation, and the experimental results proved that the proposed algorithm is accurate and effective. Show more

Keywords: Recommendation algorithm, collaborative filtering, course selection system

DOI: 10.3233/JCM-226350

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 22, no. 6, pp. 2173-2184, 2022

Authors: Li, Wenjing | Zhang, Nan | Zhu, Jinhong | Liu, Zhu | Wang, Wensheng | Li, Yan | Guo, Wenjing

Article Type: Research Article

Abstract: The Internet of Things has a large number of terminal devices and a wide range of deployment. This feature has higher requirements for reliable transmission and parallel connection, and is more prone to network congestion resulting in the loss of power information flow and excessive delay. The traditional congestion control algorithm is not suitable for the high concurrent mass heterogeneous iot terminal access control and mass information flow storage control. In this paper, the Transformer BBR algorithm is proposed, which is a congestion control algorithm based on BBR deep reinforcement learning combined with Transformer’s excellent long-term prediction ability. In the …BBR algorithm bandwidth detection stage, transformer model is used as an agent to detect the network state and map it to the congestion window, so as to find the network changing state in time and make the corresponding decision action. Firstly, the congestion control strategy is learned in the simulation network environment, and then the efficiency is verified in the simulation environment. Finally, the experiment shows that the algorithm can reduce the delay while ensuring good bandwidth performance, and is superior to the main application algorithms in network throughput. Show more

Keywords: Congestion control, deep reinforcement learning, transformer, web caching

DOI: 10.3233/JCM-226352

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 22, no. 6, pp. 2185-2199, 2022

Authors: Gao, Yun

Article Type: Research Article

Abstract: In view of the current new energy vehicles only implement torque control on the drive motor, resulting in the engine speed fluctuation, affecting the vehicle running stability and reducing the engine efficiency and energy saving effect, a new energy vehicle engine speed control method based on Internet of vehicles technology is proposed. The battery and operation data are obtained through the sensor of the new energy vehicle Internet of vehicles, and the data are controlled and transmitted by the controller area network. The overall external dynamic characteristics of the engine are analyzed by using the average value model. According to …the principle of engine dynamic system, the throttle intake manifold model, combustion torque model and power output sub model are constructed respectively. The speed is controlled by double working points According to the variable parameter PID control of the engine, the load prediction is introduced to optimize the speed control, and the internal pressure value of the accumulator is obtained through the SOP value to realize the speed control of the new energy vehicle engine. The experimental results show that the engine speed control method can effectively improve the energy-saving effect and efficiency of the engine, reduce the engine speed fluctuation, and improve the vehicle running stability under the condition of meeting the driver’s torque demand. Show more

Keywords: Internet of vehicles technology, new energy vehicles, engine, speed control, quality conservation

DOI: 10.3233/JCM-226355

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 22, no. 6, pp. 2201-2215, 2022

Authors: Yi, Yunyun | Wang, Jinbao | Ding, Xingtao | Li, Chenlong

Article Type: Research Article

Abstract: MFF-Net (a multi-scale feature fusion convolutional neural network) was designed to improve the recognition rate of handwritten digits. The low-level, middle-level and high-level features of the image were first extracted through the convolution operation, and then the low-level and intermediate features were further extracted through different convolutional layers, later directly fused with the high-level features of the image with a certain weight, and then processed by the full connection layer. By adding a batch normalization layer before the activation layer, and a dropout layer between the full connection layers, the accuracy and generalization capacity of the network are improved. At …the same time, a dynamic learning rate algorithm was designed, with which, the trained network accuracy was significantly improved as shown in the experiments on the MNIST data set. The accurate rate could reach 99.66% through only 30 epochs training. The comparison indicated that the accuracy of the network model is significantly higher than that of others. Show more

Keywords: Convolution, MNIST, activation layer, dynamic learning, dropout

DOI: 10.3233/JCM-226356

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 22, no. 6, pp. 2217-2225, 2022

Authors: Zheng, Xiaolong | Pan, Li | Lu, Bin | Jin, Yuanyuan

Article Type: Research Article

Abstract: Library is an important part of the public cultural service system. Library policy is a major force that can not be ignored. As the carrier of cultural inheritance, library plays an important role in cultivating and practicing core values and promoting civilized practice in the new era. Excavating the theme of the library is the basis for determining the development and service direction of the library. The library policy is facing difficulties such as unclear construction direction and inadequate guidance. Under this background, the research on China’s library policy is carried out. With the library as an example, the topic …mining and quantitative analysis of library policies in the eastern, central, and western regions of my country from 2011 to 2020 were conducted using the LDA topic model. Meanwhile, the differences between the three regions were investigated. The results demonstrate that: (1) In terms of quantity, policy texts in the eastern region account for more than half of them; (2) Regarding keywords, high-frequency words mainly include culture, openness, and information in the eastern region, numbers, resources, and reading in the central region, and students, teaching, and learning in the western region; (3) The hot topics in the eastern region involve library government affairs, library digital resources, and library service mode, that is, strengthening the construction of library digital resources and improving service level with an open attitude; (4) The hot topics in the central region contain library management, library student training, and library security, suggesting that the aspects of internal management and system security are emphasized to train students and guide the modernization of the library; (5) The hot topic in the western region includes the construction of two libraries in one station for library evaluation management and library procurement, implying to promote library reform from the bottom up and make crucial arrangements for creating a new situation for grass-roots libraries. On this basis, the policy support of government departments for library development in the future should focus on formulating regulations and rules under the Library Law, establishing a dynamic balance between supply and demand, and enhancing exchanges and cooperation between libraries in the east, middle, and west. Show more

Keywords: LDA topic model, policy text, library, quantitative evaluation

DOI: 10.3233/JCM-226360

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 22, no. 6, pp. 2227-2241, 2022

Authors: Wang, Lei

Article Type: Research Article

Abstract: Speech denoising refers to people finding useful information in noise-affected speech data and processing it. This technology is an important part of speech signal processing technology. With the continuous progress of science and technology, its application in various fields is gradually improving, among which voice noise reduction technology has also been well developed. Especially in recent years, with the rapid development of artificial intelligence science and technology, anti-network speech denoising technology based on deep learning has been derived. Compared with traditional speech denoising techniques, it has better performance in resolving speech data distortion and denoising results. However, in practical applications, …this method still has some shortcomings, such as: some unique noises are not removed, and the effective information extraction is distorted under the background of high-intensity noise. In response to these outstanding problems, this research is based on the anti-network speech denoising technology, combined with the Wiener filter speech denoising algorithm, and applies artificial intelligence technology to network security technology management. In this paper, two algorithms, COVL and SSNR, are used to compare the original input speech data signal with noise and the speech data signal preprocessed by Wiener filtering. The additional information is input into the generation network and the discriminant network, and the additional information is used to guide the data generation. The least squares loss function of the binary coding algorithm is used to replace the cross entropy loss function, so that the original discriminant network loss function is not changed, which improves the accuracy of discrimination. This improved technology is superior in terms of speed, productivity and improved accuracy. While building the system, mature network technologies and equipment applications are fully applied, and speech de-noising technology is used for network security situation assessment and prediction simulation tests. The simulation test results show that the network security situation assessment is reasonable and effective, and the prediction is accurate in real time. Show more

Keywords: Speech denoising, artificial intelligence, network security, application of safety management

DOI: 10.3233/JCM-226368

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 22, no. 6, pp. 2243-2255, 2022

Authors: Miao, Leigang | Niu, Yuanyuan

Article Type: Research Article

Abstract: Based on the upgrading of electronic components, communication and computer technology have made rapid progress. Neural network technology which mainly relies on the simulation of animal nerves, realize large-scale node information processing functions. Signal processing can complete the processing of various types of signals to obtain key data. With the further shortage of global energy, countries have begun to pay attention to the development of energy. As one of the traditional energy supply methods, coal mines have received a lot of financial support from the government. However, coal mine safety accidents have always been the focus of many enterprises and …governments. In the process of coal mine development, there are many electrical equipment, and there are many changes in the underground environment. The problems of flooding, subsidence, and rodents biting off the line cause the paralysis of the electrical system and eventually lead to safety accidents in coal mine development. The neural network technology, can add all the electrical equipment in the mine operation, and to the network for analysis, and the signal processing technology can centrally process the signals of a variety of electrical equipment, and analyze the abnormal signals sent by the electrical equipment, and finally realize the prediction of electrical accidents. This paper firstly introduces the neural network and signal processing technology used in the text. Using the examples of hidden safety hazards in mining areas discovered during the team’s inspection as a basis, and combining with the actual situation in our country, these cases are classified. Next, using literature analysis and comparative research methods to analyze the problems existing in the current coal mine electrical safety management and accident prevention. A programme of safety management and accident prevention. The O-Net monitoring system constructed by the institute has its own unique advantage that it has more inputs than other networks, and its network structure is more complex and diverse, which of course also shows that it has more functions than other networks. The results of the scheme test show that the scheme can effectively reduce the probability of electrical safety accidents in coal mines, and at the same time effectively improve the efficiency of electrical safety management in coal mines. After multiple cycles of verification, the algorithm designed in this study has a very good effect in improving the safety of electrical equipment in coal mines, and the risk factors of each work have been effectively controlled, which is worthy of promotion in coal mines with similar environments. Show more

Keywords: Coal mine safety, neural network technology, signal processing technology

DOI: 10.3233/JCM-226370

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 22, no. 6, pp. 2257-2266, 2022

Authors: Luo, Hongxuan | Wei, Ling | Pan, Tingzhe | Li, Xiang

Article Type: Research Article

Abstract: Considering the limitation of computing resources, resource over-reserving, and virtual machine stability, this paper proposes an adaptive dynamic management method for virtual machine resources in cloud/fog computing system. The cloud/fog computing task processing process is modeled in the case of the resource constraints in cloud or fog computing node. According to the tradeoff of resource utilization efficiency and system stability, the virtual machine resources are scheduled elastically to realize the on-demand use of cloud/fog computing resources. The experimental results show that the proposed method can effectively improve the resource efficiency of cloud/fog computing and guarantee the quality of service under …the dynamic task workload. Show more

Keywords: Fog/cloud computing, resource scheduling, on-demand use, quality of service guarantee

DOI: 10.3233/JCM-226202

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 22, no. 6, pp. 2267-2278, 2022

Authors: Wang, Chen | Rong, Xiao | Dou, Zhenhai | Liu, Yawei | Shao, Kaiguang | Liu, Lianxin

Article Type: Research Article

Abstract: Distributed power grid integration contributes to both the reduction of greenhouse gas emissions and the protection of the environment. Nevertheless, the uncertainty and volatility associated with the production of clean renewable energy adds additional challenges to microgrid dispatch. The paper presents an adaptive mutant bird swarm algorithm and suggests a comparison mechanism based on population fitness variances and optimal values in order to overcome the shortcomings of BSA, in particular its tendency to self-correct into local optimum and slow convergence speed. First, the algorithm determines if the population is in the local optimal state. The local optimal individual is then …subjected to Cauchy mutation in order to determine the optimal value again. This improves the accuracy and speed of the BSA. Based on simulation results, the improved algorithm has higher optimization accuracy and faster optimization speed, which demonstrates the effectiveness and advancement of the algorithm proposed in this research. Show more

Keywords: Micro grid, optimal scheduling, bird swarm algorithm, adaptive mutation, distributed power

DOI: 10.3233/JCM-226338

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 22, no. 6, pp. 2279-2293, 2022

Authors: Zhang, Shuo | Zou, Hua | Qiao, Zhicheng | Xu, Yan | Sun, Jian | Qin, Hao

Article Type: Research Article

Abstract: In order to achieve carbon peak and neutrality goals, this study takes product innovation as the breakthrough point, draws lessons from the replication dynamic thought of the biological evolution process, and uses game evolutionary algorithm to analyze the gradual stability of enterprises, governments and users. Although the environment does not actively participate in the game, its benefits directly affect the strategic choices of the other three parties. Therefore, the environmental benefit is regarded as one of the important variables to establish a game model for solving and simulation, and analyze the key variables affecting the game. This paper discusses the …game situation of green product innovation in the evolutionary system for promoting “four-party satisfaction”. The concepts of proactive preventive cost and passive loss cost are redefined and put forward. Research shows that: (1) Proactive preventive cost plays a positive role in promoting green product innovation with “four-party satisfaction”. (2) Increasing subsidies for purchasing green products, reducing the price of green products, increasing purchase tax on non-green products, and increasing government investment in environmental protection publicity and green upgrade of infrastructure will all increase users’ willingness to buy green products. (3) The government formulates reasonable reward and punishment measures to provide necessary financial support for enterprises, so that the final income of enterprises from green product innovation is greater than that from traditional product innovation. It will encourage enterprises to carry out green product innovation. Show more

Keywords: Evolutionary game algorithm, equilibrium stability, product innovation

DOI: 10.3233/JCM-226334

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 22, no. 6, pp. 2295-2317, 2022

Authors: Sun, Yong | Niu, Jinhua | Xu, Huixuan | Liu, Yang | Yang, Yiwei | Xu, Feng

Article Type: Research Article

Abstract: An experimental and simulation study was carried out on the air supply system of the electric heating solid heat storage unit, aiming to improve the uniformity of the air supply system, thereby increasing the overall heating efficiency of the solid heat storage unit. The experiments show that non-uniform air distribution of the air system may cause non-uniform heat release of the heat accumulator, and the uniformity of the air supply system is greatly affected by the air supply structure and air inlet. By establishing a model of the heat storage device and conducting numerical simulation, the air distribution law of …the air supply system was studied. According to the study results, the uniformity index of the air system was effectively improved by increasing the air cabin width and the air inlet angle, and adding a static pressure box at the air supply outlet, so that the flow velocity distribution of the air supply system was more uniform, which is of great significance to the overall optimization of the solid heat storage and heating system. Show more

Keywords: Electric heating solid heat storage unit, flow velocity distribution uniformity index, experiments, numerical simulation

DOI: 10.3233/JCM-226233

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 22, no. 6, pp. 2319-2342, 2022

Authors: Zhang, Lihui | Lu, Wei | Zhang, Caiqing

Article Type: Research Article

Abstract: As the technical demand-supply text information increases rapidly in electric power technology transfer, traditional matching methods could no longer meet the need. To solve this problem, this paper proposed a new technical demand-supply matching method based on electric power technical field feature. First, the improved TF-IDF algorithm was used to extract technical field feature, then scientific and technological achievements with higher relevancy were retrieved based on technical field feature to build a background library of electric power technological achievements, and the matching degree of electric power technological achievements based on word vector was used to verify the matching efficiency of …this method. We adopted the China smart grid technical transaction service platform and the text message of electric power technical demand and technological achievements on Keyi net for application, and the results indicate this method has raised the matching efficiency by 23.4% compared to traditional methods. In this paper, a new idea of taking technical field feature as the demand-supply matching basis of electric power technology transfer platform was proposed, which opens a new perspective for the research of demand-supply matching efficiency on electric power technology transfer platform, helps to promote the matching efficiency of technical demand and technological achievements, and further raises the success rate of electric power technology transfer. Show more

Keywords: Technology transfer, technical demand-supply matching, technical field feature

DOI: 10.3233/JCM-226229

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 22, no. 6, pp. 2343-2357, 2022

Authors: Wei, Zixiang | Hao, Yanjun

Article Type: Research Article

Abstract: Insulator determines the insulation level and power supply reliability of transmission lines. The traditional operation and maintenance method of insulators has a large workload. This paper presents an insulator recognition and fault diagnosis system based on image recognition and machine learning. Firstly, the composite insulators in complex backgrounds have been identified by Faster RCNN algorithm, which helps to extract the image of insulators by drone shot. Then, the cracking of umbrella skirts has been carried out by means of image processing. Also, the contamination of composite insulator umbrella skirts is also identified. The appropriate feature quantity by Fisher’s discrimination is …recommended, and the insulator contamination level has been identified by S component. Lastly, analyzing the infrared image of the insulator provides the basis for the normalization of insulator temperature rise detection results in different environments. Insulator image autonomous recognition and defect intelligent detection, which is based on deep reinforcement learning, is helpful for the operation, maintenance and repair of line insulators. Show more

Keywords: Insulator, image recognition, defect detection, deep learning, insulator cracking

DOI: 10.3233/JCM-226224

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 22, no. 6, pp. 2359-2374, 2022

Authors: Cheng, Zhao | Chen, Guanlin | Weng, Wenyong | Lu, Qi | Yang, Wujian

Article Type: Research Article

Abstract: Recently, AWD-LSTM (ASGD Weight-Dropped LSTM) has achieved good result in the language model, and many AWD-LSTM based models have obtained state-of-the-art perplexities. However, in fact, large-scale neural language models have been shown to be prone to overfitting. In AWD-LSTM original paper, the author decided to adopt the way of retraining calling finetune to get a better result. In this paper, we present a simple yet effective parameter rollback mechanism for neural language models. And we introduce the parameter rollback averaged stochastic gradient descent (PR-ASGD), wherein the parameter “step” in ASGD will decrease according to a certain probability. Using this strategy, …we achieve better word level perplexities on Penn Treebank: 56.26 based on AWD-LSTM model and 53.57 based on AWD-LSTM-MoS (AWD-LSTM Mixture of Softmaxes) model. Show more

Keywords: Optimizer, language model, machine learning

DOI: 10.3233/JCM-226215

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 22, no. 6, pp. 2375-2385, 2022

Authors: Sun, Yong | Xu, Hui-Xuan | Liu, Yang | Xue, Ke-Li | Shi, Yong-Jiang

Article Type: Research Article

Abstract: In recent years, in response to the call for energy conservation and emission reduction, the air source heat pump systems have been widely applied in regional centralized heating engineering.However, due to the existence of cold island effect, the heat pump unit operation in winter has the problems of low efficiency, high operation cost and insufficient production.This paper takes the heat source station combined with gas source heat pump and electric boiler as an example, and its heat pump unit array was simulated and calculated by analyzing relevant test data and using the numerical calculation method. Some technical measures were put …forward to improve the cold island effect, and then the advantages and application scope of these measures are also analyzed. Show more

Keywords: Air source heat pump, regional heat supply, cold island effect, numerical simulation, technical measures

DOI: 10.3233/JCM-226208

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 22, no. 6, pp. 2387-2411, 2022

Authors: Hao, Ying | Guo, Ming-Shun | Zeng, Hui

Article Type: Research Article

Abstract: Considering the influence of new energy vehicle enterprises innovation input is affected by a variety of non-linear and uncertain factors, an automatic coding machine mixed with RBF neural network model is presented in this paper, and the Gaussian distribution of training data optimization method and the Gaussian transfer function training module are put forward to make innovation input higher prediction precision and stronger universality. By comparing the prediction data of the proposed model with that of the traditional neural network model, the accuracy of the improved model is verified. Therefore, the proposed model can provide theoretical basis and decision support …for technological innovation decision-making of new energy vehicle enterprises. Show more

Keywords: Hybrid neural network, gaussian distribution, new energy vehicle, innovation input, prediction

DOI: 10.3233/JCM226488

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 22, no. 6, pp. 2413-2423, 2022

Authors: Sun, Gefei

Article Type: Research Article

Abstract: Quantitative investment can manage enterprise assets better to obtain higher revenues. This paper analyzed quantitative investment prediction using machine learning algorithms. First, the support vector machine (SVM) algorithm was introduced, and stock changes were predicted by the SVM algorithm. Then, the feature factors in stock data were extracted by maximum information coefficient (MIC) as the input of the SVM algorithm. Finally, the performance and backtest results of the SVM algorithm was analyzed. It was found that the SVM algorithm had a good performance, and its F1-score was 0.9884, which was better than C4.5 and random forest algorithms. In terms of …backtesting, the portfolio built based on the prediction results of the SVM algorithm obtained a higher annualized return rate when the number of stocks was small; when the number of stocks was 10, the portfolio built based on the SVM algorithm had an annualized return rate of 83.67%, a smaller maximum retracement, and a higher Sharpe ratio than the other algorithms, which balanced the risk and return well. The results demonstrate the reliability of the SVM algorithm in predicting quantitative investment, which is beneficial to achieving the optimization of enterprise asset management. Show more

Keywords: Machine learning, quantitative investment, asset management, support vector machine, maximum retracement

DOI: 10.3233/JCM-226478

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 22, no. 6, pp. 2425-2433, 2022