Journal of Intelligent & Fuzzy Systems - Volume 37, issue 1

Authors: Huang, He | Deng, Haojiang | Sheng, Yiqiang | Ye, Xiaozhou

Article Type: Research Article

Abstract:  Deep learning methods have been widely used in today’s network security systems for their outperforming in detecting rates of the patterns of anomalous network actions. Particularly, in the field of malware traffic classification, time reduction for a detecting process is of great importance and can stop network damage at an early stage. To achieve a balance between the detection rate and time consumption, practical structures of relative systems are usually simple, complicating the application of appropriate accelerating methods. In this study, we propose a novel ant-colony -based clustering algorithm, which can efficiently select the most valuable data points for the …next step of learning. In addition, to take advantage of the widely-used convolutional neural network architecture, we defined the mapping-image of each raw traffic data, and then transformed the intrusion detection problem into an image recognition problem. Before each training iteration, we applied the clustering algorithm to locate the most-featured part of each specific type of network traffic. Next, we utilized this featured part in the training, by considering its depth and shallow information, so that its precision and robustness can be improved. Preliminary experiments demonstrate that our method not only achieves high-detection-rate results but also manages to utilize much less processing time with proper parameter tuning of the neural networks. Show more

Keywords: Deep learning, convolutional neural network, intrusion detection system, network anomaly detection, heuristic clustering

DOI: 10.3233/JIFS-179096

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 1, pp. 409-423, 2019

Authors: Yang, Xiaodong | Lin, Xiaoxia | Lin, Xiaole

Article Type: Research Article

Abstract: With the continuous development of internet and information technology, human beings need to process a lot of information and data. When processing a large amount of information, data mining technology must be used. In order to better mine the required data information quickly based on condition matching, an optimized Apriori and FP - Growth association rule mining algorithm is proposed. Based on the algorithm flow and evaluation model, an optimization and up-date scheme is proposed, an effective data transmission evaluation model is established by effectively evaluating the state of data analysis, and the corresponding evaluation results are given. By introducing …the idea of improved decomposition database to reduce the collection of infrequent databases, the algorithm adaptability is improved. In order to verify the feasibility and reliability of the method, the case experiment is demonstrated. Based on the experimental results, the algorithm is more effective in actual operation efficiency and data mining precision. Show more

Keywords: Apriori algorithm, FP-Growth algorithm, data minin

DOI: 10.3233/JIFS-179097

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 1, pp. 425-432, 2019

Authors: Gang, Wang

Article Type: Research Article

Abstract: Under the tide of artificial intelligence, automobile, the most commonly used means of transportation, is about to enter a new era of automation and driverless driving. Road testing of driverless cars designed by many companies in China and other countries has begun and is imminent. However, there is still a gap in the study of the legal adaptation of driverless vehicles, especially the existing road traffic safety laws for driverless enterprises. To promote the rapid application of new technology of driverless vehicles, this paper considers the influence of people, vehicles, roads and traffic management on driverless vehicles, and constructs a …highway safety evaluation model based on support vector machine. In 2003, the model parameters were optimized to reduce the possible criminal dilemma of driverless vehicles. The simulation results show that the research has good theoretical value and practical space. Show more

Keywords: Intelligent algorithm, driverless vehicle, criminal law, research

DOI: 10.3233/JIFS-179098

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 1, pp. 433-440, 2019

Authors: Xueying, Tian | Panke, Nie

Article Type: Research Article

Abstract: This article has been retracted, and the online PDF has been watermarked “RETRACTED”. A retraction notice is available at https://doi.org/10.3233/JIFS-219218 .

DOI: 10.3233/JIFS-179099

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 1, pp. 441-454, 2019

Authors: Wang, Rui | Yang, Shuchen | Wang, Dongxue

Article Type: Research Article

Abstract: Active vibration control is a new subject developed in the last twenty years. It mainly studies the theory, method and measure of active vibration control of structures. After introducing the linear quadratic optimal control algorithm, the numerical simulation of the linear quadratic optimal control for a piezoelectric flexible cantilever beam is carried out. The model of the flexible cantilever beam is established firstly, including the differential equation of motion, the moment equation of the actuator and the output equation of the sensor. Then the optimal feedback gain matrix of the system is obtained by using the linear quadratic optimal control. …In this paper, genetic algorithm is used to optimize the above parameters of BP neural network, and the improved BP neural network is applied to the study of nonlinear model of dynamic coal blending. A method based on piezoelectric self-sensing method is proposed as a test method. A piezoelectric wafer of piezoelectric bimorph is used as the sensing element, analyzing the relationship between the acceleration parameters of the piezoelectric bimorph and the induced charge generated by the sensing element, and a test circuit device for driving force is designed. The method uses genetic algorithm to calculate the control force online and uses the neural network to simulate the dynamic characteristics of the plate, thus replacing the cantilever plate for dynamic analysis. The system fully utilizes the characteristics of genetic algorithms and neural networks and is a new type of vibration control system with promising future. Show more

Keywords: Piezoelectric intelligent structure, neural network, driving force

DOI: 10.3233/JIFS-179100

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 1, pp. 455-465, 2019

Authors: Yu, Wang | Huafeng, Wang

Article Type: Research Article

Abstract: Macroeconomics is a very complex and huge system. With the improvement of China’s market economy, it is of great theoretical significance and practical value to apply quantitative economics methods and models to study the macroeconomic state and forecast the economic development trend. The development of regional economy is restricted by natural conditions and social and humanistic conditions, and it is a complex system with many factors and levels. By using grey system theory, data processing can reduce its randomness and strengthen the inherent trend of data, so it is possible to use as few data as possible to establish a …model describing economic system. Through empirical test, the author analyses the main factors of unbalanced regional economic development and puts forward the comparative advantages of regional development. According to the simulation results, the predicted results are stable and reliable. The conclusion of the study has a certain reference value for the formulation of macroeconomic policies. By strengthening the guidance of government classification, the regional economic disparity will be narrowed continuously. Show more

Keywords: Grey relevance, complex set, economic indicators, empirical test

DOI: 10.3233/JIFS-179101

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 1, pp. 467-480, 2019

Authors: Wang, Hongli | Islam, Kamrul

Article Type: Research Article

Abstract: Tracking audit of poverty alleviation policy is an important guarantee to win the battle against poverty. Effective prevention and control of audit risk in tracking audit of poverty alleviation policy is the key to ensure the improvement of audit quality. According to the characteristics of financial audit, this paper analyzes the main factors affecting the operation of loan enterprises, puts forward a neural network model for financial audit, and gives the solution of the model. This paper takes poverty alleviation audit as an example, centering on the goal of full coverage of the audit, and based on poverty alleviation data, …integrating relevant data in relevant fields to build poverty alleviation fund audit, so as to achieve full coverage of poverty alleviation audit. Utilize emerging technologies, give full play to the role of full coverage of audit supervision and supervision on precision poverty alleviation, and participate in project consulting and auditing in advance, real-time online tracking audit, and post-performance performance evaluation audit. We will promote the construction of accurate poverty alleviation information, strengthen economic responsibility audits, and more effectively monitor the authenticity of poverty alleviation funds, effectively implement poverty alleviation projects, and achieve accurate poverty alleviation efficiently. The model can better help the auditors to accurately determine the basic status of the audit object and provide a strong guarantee for quickly determining the audit focus. Show more

Keywords: BP neural network, poverty alleviation funds, audit mode

DOI: 10.3233/JIFS-179102

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 1, pp. 481-491, 2019

Authors: Liu, Xin | Zhou, Yanju | Wang, Zongrun

Article Type: Research Article

Abstract: For the acquisition of user behavior preference in social network, usually a data mining will be conducted on the nearest neighborhood users or latestprojects based on the user’s historical behavior data, so as to find similar behaviorrelationship for quantitative analysis; it can also focus on the awareness on the user-related context information based on cognitive psychology, so as to find its internal links forthe potential mining. However, these methods ignore the intrinsic link between the browsing behavior and the preferred topics in the user link connection, resulting in the limited precision and accuracy of the preference acquisition. Inspired by the …theory of complex network link prediction and the topic model, anacquisition method for users’ browsing behavior preference was proposed in this paper. In the multi-dimensional network link environment, by measuring the importance of the node via network centrality and search the social network link via setting the similarity threshold, the real-time multi-link information and the big data about users’ browsing under each link were acquired, then the data were filteredand cleaned by using adjustable parameters. On this basis, according to the least squares criterion the data underwent a fusion and were used to construct a data node distribution model for user browsing behavior, then the frequent feature items of user browsing behavior preference were extracted. Based on the extracted feature terms, the variational Bayes approximation reasoning method was used to construct the preference topic model. Finally, the hierarchical VSM model representation method was used to establish the preference acquisition model of user browsing behavior, and the model was updated in real time by user feedback processing mechanism. The experimental results on the real data set showed that the link search method and the preference topic model provided by this paper are accurate and efficient. Compared with the classical cooperative filtering method and the context-awareness method, the precision, accuracy and effectiveness of the preference acquisition model provided this paper are significantly improved, and its adaptability has been significantly strengthened. Show more

Keywords: Social network link, topic model, user browsing behavior, preference acquisition

DOI: 10.3233/JIFS-179103

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 1, pp. 493-508, 2019

Authors: Ji, Linzhang | Cheng, Daolai | Yi, Chuijie | Zick, Sandra

Article Type: Research Article

Abstract: At present, the CAAC has established the only “Aircraft Cabin Sound Information Sample Library” in China, which provides strong support for the theoretical analysis method based on the CVR non-discourse sound blind source separation. The separation of aircraft background acoustic blindness based on EEMD-ICA is studied. The performance of different algorithms for the separation of CVR non-discourse background acoustic typical observation signals is compared, and an incompletely constrained adaptive natural gradient algorithm is found for signals that change drastically over time and have a near-zero amplitude over a more extended period. In addition, when there is redundant information or noise …on the CVR background acoustic signal, an independent component analysis method is used to reduce the dimensionality of the observed signal, which is essential for extracting valuable information from confounded signals and provides a reference for dealing with changing mixed signals. Show more

Keywords: EEMD-ICA, aircraft, Background acoustic blind separation

DOI: 10.3233/JIFS-179104

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 1, pp. 509-516, 2019

Authors: Han, Kaiyan | Liu, Xiaoping | Ping, Shao-kang | Wang, Ping

Article Type: Research Article

Abstract:  The research is carried out the kinematics analysis of combined technical actions in hip-hop movements by the methods of three-dimensional analysis of motion biomechanics. Based on three aspects of the movement track, motion characteristics and core technical action analysis, the results show that: the facet joint play the role of driving action; The movement can be changed by changing the direction of the force when connected; And the body should be reduced the buffer in the way the fingertips or toes touching the ground first when doing actions.

Keywords: Hip-hop movement, bio-mechanics, three-dimensional analysis, fuzzy system

DOI: 10.3233/JIFS-179105

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 1, pp. 517-525, 2019