Journal of Intelligent & Fuzzy Systems - Volume 35, issue 3

Authors: Wang, Longge | Yu, Junyang | Qiao, Baojun

Article Type: Research Article

Abstract: This study aims to use neural network theory to analyze and evaluate computer network security. Firstly, the evaluation model of computer network security was given based on relevant literature, and the corresponding index system was constructed, including 19 indicators of management security, physical security, and logical security. Then, the index normalization standard was proposed and the index security level was set. Finally, computer network security was evaluated according to the neural network. Results show that security management strategy has the greatest impact on computer network security, followed by routing control and data encryption.

Keywords: Neural network, computer, network security, intelligent evaluation

DOI: 10.3233/JIFS-169643

Citation: Journal of Intelligent & Fuzzy Systems, vol. 35, no. 3, pp. 2887-2891, 2018

Authors: Zhang, Bo | Zhang, Jianwei | Guo, Konghui | Ding, Haitao

Article Type: Research Article

Abstract: Driverless vehicles interacting with other traffic participants, such as cars, pedestrians and bicycles inevitably will inevitably interact in complex traffic environment. During the interaction, all potential collisions must be avoided to ensure driving safety. Based on the model predictive control, this paper analyzed the active obstacle avoidance algorithm for unmanned vehicles, and proposed a collaborative trajectory planning program for unmanned vehicles with multiple collision and collision management. The coordinated collision avoidance rules based on angle change were used to solve the consistency problem of distributed collision avoidance. The simulation results show that the scheme can effectively solve the multiple collision …problems between UAVs. Show more

Keywords: Model predictive control, unmanned vehicle, active obstacle avoidance algorithm, collision control

DOI: 10.3233/JIFS-169644

Citation: Journal of Intelligent & Fuzzy Systems, vol. 35, no. 3, pp. 2893-2900, 2018

Authors: Zhou, Yongwei | Fan, Hehua

Article Type: Research Article

Abstract: Faced with the problems of low production efficiency and unreasonable industrial organization exist in the development of agriculture, this paper studied the multi-objective optimization of sustainable agricultural industrial structure based on genetic algorithm in order to optimize the allocation of agricultural industrial structure. First of all, this paper expounded the current agricultural development background, and then put forward the research status of multi-objective optimization algorithm, based on which points out the advantages of genetic algorithm. Then, establish the model system that is based on the optimal allocation of industrial structure. Use the improved genetic algorithm to solve the problem, …and modify the operator design to obtain the optimal algorithm for the sustainable agricultural optimization sequence. The results of the algorithm evaluation show that the optimized industrial structure benefit value and sustainability both have been improved. Show more

Keywords: Sustainable agriculture, multilevel objective optimization, genetic algorithm, industry institution

DOI: 10.3233/JIFS-169645

Citation: Journal of Intelligent & Fuzzy Systems, vol. 35, no. 3, pp. 2901-2907, 2018

Authors: Rui, Cai

Article Type: Research Article

Abstract: The research of face recognition began in the 70s of last century. With the rapid development of science and technology and computer technology, it has been used in the application of property management, which has become a new research direction. Based on this, the research status of intelligent property and face recognition at home and abroad was investigated. On this basis, the concept and principle of face recognition technology were analyzed, and PCA algorithm was proposed for face recognition. According to the basic theory of PCA algorithm, it was applied to face recognition technology. The principle of PCA algorithm was …proposed, and the principal component analysis method was deduced and applied to face recognition. According to the performance of PCA algorithm in face recognition technology, a new wavelet transform method was used in face recognition algorithm. After extracting the facial feature vector, the wavelet transform method combined with PCA algorithm was obtained. Finally, the proposed algorithm was applied to intelligent residential property management system. The results show that the algorithm can effectively improve the recognition accuracy and can meet the design requirements, which provides a theoretical basis for the subsequent system research. Show more

Keywords: PCA, algorithm, face recognition, intelligent property

DOI: 10.3233/JIFS-169646

Citation: Journal of Intelligent & Fuzzy Systems, vol. 35, no. 3, pp. 2909-2919, 2018

Authors: Fei, Xianju | Tian, Guozhong

Article Type: Research Article

Abstract: In previous studies, due to the sparsity and chaos of distributed data, such a result would lead to a local convergence phenomenon by using PSO algorithm, resulting in low accuracy of data mining. So this time we proposed a data mining algorithm based on neural network and particle swarm optimization. At the beginning, we calculated the global kernel function of differentiated distributed data mining and mixed to build the mining decision model. The training error was used as the constraint condition of mining optimization to realized data optimization mining. The results showed that the differential distributed data mining with this …algorithm has higher accuracy and stronger convergence. Show more

Keywords: Neural network algorithm, particle swarm optimization algorithm, data mining algorithm

DOI: 10.3233/JIFS-169647

Citation: Journal of Intelligent & Fuzzy Systems, vol. 35, no. 3, pp. 2921-2926, 2018

Authors: Gu, Deping

Article Type: Research Article

Abstract: At this stage, the technical and tactical information acquisition technology has become the key factor to improve the performance of athletes. In this paper, “manual + automation” information collection method was selected. At the same time, in order to improve the speed of information collection, a kind of intelligent prompt automatic completion algorithm was designed and proposed. In the algorithm, the optimization algorithm was improved in view of the poor convergence in the original algorithm, and then the intelligent completion algorithm with more restrictive was further proposed. By collecting the standard document of dynamic standard information and embedding the basic …video file, the algorithm was beneficial to the algorithm and automatic completion and intelligent prompt visual features in the video retrieval and analysis. In addition, in terms of technology, the video semantic description was carried out based on the AVI format, and the video retrieval and video analysis based on sports tactical competition were realized, thus providing complete technical support for coaches and athletes in scientific competitions, and improving the level of athletes’ skills and tactics. Show more

Keywords: Intelligent algorithm, information acquisition, video retrieval

DOI: 10.3233/JIFS-169648

Citation: Journal of Intelligent & Fuzzy Systems, vol. 35, no. 3, pp. 2927-2936, 2018

Authors: Xu, Xin

Article Type: Research Article

Abstract: With the network technology development and the current attention to network security, the intrusion detection technology of the network system research has being regarded more important. The previous system intrusion detection section has not been able to meet and adapt to the needs of the current rapid development of the network era. The construction of the framework of intrusion detection system is our primary job. This research adopts the genetic attribute reduction algorithm based on rough set and neural network intrusion detection system simulation analysis, through the simple computer algorithm and system simulation analysis of intrusion mode simulation model establishment. …The results show that the study has made great success. Show more

Keywords: Rough set, genetic attribute reduction algorithm, neural network, intrusion detection system

DOI: 10.3233/JIFS-169649

Citation: Journal of Intelligent & Fuzzy Systems, vol. 35, no. 3, pp. 2937-2942, 2018

Authors: Ma, Xianrui | Zeng, Deheng | Wang, Runyuan | Gao, Jingxin | Qin, Beibei

Article Type: Research Article

Abstract: The precision of price appraisal is directly linked to the sound development of a market-oriented economy and public benefit. Market comparison approach is a widely used price-appraisal algorithm. However, when the sample size is small, the computing precision of the market comparison approach is severely impaired. To realize precise, intelligent computing under the conditions of a small sample size and a low degree of proximity between samples and the object to be evaluated, this study adopted grey correlation and fuzzy mathematics to optimize the market comparison approach for price appraisal. The proposed algorithm used grey correlation analysis to quantify the …weight of various attributes influencing price appraisal. The price correlation between samples and the object to be evaluated was confirmed. The fuzzy mathematical method was then used to obtain the relative weight of samples. The proposed intelligent price-appraisal algorithm was constructed to improve the market comparison approach. Finally, several residences in Hangzhou, Zhejiang province, China were chosen for an empirical analysis and for the verification of the feasibility of the improved price-appraisal algorithm. Results suggest that (1) The mean error of the algorithm is only 0.99%, indicating high computing precision; (2) When the number of objects to be evaluated is large, a computer system can be used to aid the intelligent computing and to efficiently perform intelligent computing. In conclusion, the proposed algorithm can maintain high computing precision under the conditions of a small sample size and a low degree of proximity, and the algorithm can be used as a theoretical basis to realize intelligent mass appraisal. Overall, the proposed algorithm is worthy of further development because it is highly operational. Show more

Keywords: Grey correlation, fuzzy mathematics, price appraisal, intelligent computing

DOI: 10.3233/JIFS-169650

Citation: Journal of Intelligent & Fuzzy Systems, vol. 35, no. 3, pp. 2943-2950, 2018

Authors: Zhang, Zhen | Yu, Jintian | Hu, Chunhua

Article Type: Research Article

Abstract: Studies on path dependence (PD) and lock-in have indicated several limitations, such as chaotic literature information, interdisciplinarity complexity, and evolution vagueness. In this study, literature on path dependence and lock-in are obtained from the database of Web of Science Core Collection from 2001 to 2017. The knowledge mining model of the evolution of path dependence and lock-in is constructed based on knowledge mining process and content. The evolution of this area is also explored. Results show that the evolution of path dependence and lock-in can be categorized as follows: (1) English, American, and German scholars have led the research on …path dependence and lock-in. (2) The research topics have undergone four stages. (3) The research levels have been classified as policy system (macro-level), regional economy (meso-level), and organizational path dependence (micro-level). (4) The research design can be represented as theory basis, case discussion, lock-in or reformation, and path creation. (5) The research method can be transformed from case study into lock-in mathematical modeling. A panoramic knowledge mapping of path dependence and lock-in is displayed by the research system to enhance understanding on research trajectories and future research directions. Show more

Keywords: Path dependence, lock-in, knowledge mining, evolution, knowledge mapping

DOI: 10.3233/JIFS-169651

Citation: Journal of Intelligent & Fuzzy Systems, vol. 35, no. 3, pp. 2951-2963, 2018

Authors: Xia, Jiali | Li, Guangquan | Cao, Zhonghua

Article Type: Research Article

Abstract: Intelligent exercise recommendation is a research focus in the field of online learning that can help learners quickly find exercises suitable for them from the exercise bank. However, exercise recommendation differs from product or film recommendation because of some special requirements. First, the recommended exercises must cover all knowledge points geared toward the learning objective of the learner. Second, the difficulty of exercises must match the knowledge level of the target learner. In response to the above requirements, this study proposes an exercise recommendation algorithm that integrates learning objective and assignment feedback. This algorithm considers not only the coverage of …knowledge points but also the knowledge level of learners to help them find highly suitable exercises. According to this algorithm, the learning objective of the learner must be initially identified to obtain a course knowledge set that suits his/her learning objective. Second, the understanding of the learner about the knowledge set must be judged based on the assignment feedback. Third, suitable exercises are recommended based on the knowledge level of the learner and the course knowledge structure. The proposed algorithm is experimentally verified by using a real-world dataset and by comparing it with other algorithms. The experimental results show that the proposed algorithm significantly outperforms the other algorithms in both precision and recall. Based on these results, the proposed algorithm can achieve an excellent recommendation performance. Show more

Keywords: Recommender systems, online learning, assignment feedback, course knowledge set

DOI: 10.3233/JIFS-169652

Citation: Journal of Intelligent & Fuzzy Systems, vol. 35, no. 3, pp. 2965-2973, 2018