Journal of Intelligent & Fuzzy Systems - Volume 40, issue 2

Authors: Xu, Wenhan | Bo, Hongguang | Chen, Yinglian

Article Type: Research Article

Abstract: In order to explore the impact of the system-driven supply chain, collaborative operations, and organizational characteristics on supply chain operational performance, this paper based on the system dynamics method to simulate the established information collaborative supply chain model, analyze market demand data, inventory before and after the supply chain sharing The changes of inventory fluctuations in the supply chain and related calculations are compared with the simulation results under the current model to prove the importance of implementing information collaboration in the supply chain of a large retailer-led supply chain. The research in this paper shows that with the supply …chain information collaboration model, the average value of the manufacturer’s order quantity has dropped by 30.4%. Affected by this, the dispersion coefficient has also dropped from 0.76 to 0.6, and the average number of orders in the distribution center has also dropped by 12.2%; With the supply chain information synergy model, the average value of the raw material inventory of manufacturers has dropped significantly, from 3400 in the current model to 2500 in the information synergy model, a decrease of 27%, the standard deviation has also decreased by 57%, and the dispersion coefficient has dropped from 0.98 to 0.50; The standard deviation rate of the inventory of the distribution center is 30%; from the perspective of the overall retail supply chain, the inventory has fallen by 14%, the standard deviation has fallen by 34%, and the dispersion coefficient has dropped from 0.76 in the current model to the information collaboration model. 0.6, it can be seen that the mode of supply chain information coordination has a great effect on reducing supply chain costs and improving supply chain efficiency. Show more

Keywords: System dynamics, supply chain management, information collaboration, a supply chain operating performance

DOI: 10.3233/JIFS-189347

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 2, pp. 3085-3095, 2021

Authors: Zhao, Jinghua | Lin, Jie | Liang, Shuang | Wang, Mengjiao

Article Type: Research Article

Abstract: The paper first analyzes the correlation between text sentiment values and personality traits, proves that text sentiment can have a good support effect on user personality prediction, then on this basis, a method based on CNN-LSTM is proposed, which can be used to deeply analyze the sentiment analysis capability of the model, hoping to improve the precision of sentiment classification and lay a solid foundation for the next experiment. This experiment proves that the CNN-LSTM constructed in this paper can better predict the emotional tendency of the short text of microblog, has good generalization ability, and has higher precision than …other methods. Show more

Keywords: CNN-LSTM, sentiment annotation, social media, personality

DOI: 10.3233/JIFS-189348

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 2, pp. 3097-3106, 2021

Authors: Fu, Qiang | Ma, Li | Li, Chao | Li, Zhi | Zhu, Zhengyu | Lin, Zhiran

Article Type: Research Article

Abstract: At present, the majority of sports games video adopts MPEG image technology, and MPEG video compression is the current more mainstream approach. After compression, the quality of the video will decline, and other practical problems. However, the existing detection methods of sports video scene conversion, when dealing with MPEG compressed video, are not ideal, often appear the phenomenon of missing detection and wrong detection. In order to solve this problem, this paper proposes a detection method of sports scene conversion on MPEG compressed video based on fuzzy logic. Introducing fuzzy logic into the detection method of video scene conversion is …the highlight of this method. Firstly, this paper preprocessed the video image according to the Convention. In this paper, the recognition of image features and specific extraction methods are introduced in detail, and the extraction algorithm of image color features is further optimized. For the design of the detection method, the main innovation is to fully combine the fuzzy logic and macroblock information. In the existing detection methods, different detection schemes are given for the abrupt change of video scene and the gradual change of scene. Finally, in order to verify the actual effect of the detection method in this paper, an experimental analysis based on the keyframe complexity detection method is established. After a number of experiments including the experimental results of scene transition, analysis, and processing time, through the analysis of data, a step-by-step proof of this method has good accuracy and recall. Show more

Keywords: Fuzzy logic, MPEG compression technology, scene detection; sports video

DOI: 10.3233/JIFS-189349

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 2, pp. 3107-3115, 2021

Authors: Li, Zhipeng | Li, Xiaolan | Shi, Ming | Song, Wenli | Zhao, Guowei | Yang, Ruizhu | Li, Shangbin

Article Type: Research Article

Abstract: Snowboarding is a kind of sport that takes snowboarding as a tool, swivels and glides rapidly on the specified slope line, and completes all kinds of difficult actions in the air. Because the sport is in the state of high-speed movement, it is difficult to direct guidance during the sport, which is not conducive to athletes to find problems and correct them, so it is necessary to track the target track of snowboarding. The target tracking algorithm is the main solution to this task, but there are many problems in the existing target tracking algorithm that have not been solved, …especially the target tracking accuracy in complex scenes is insufficient. Therefore, based on the advantages of the mean shift algorithm and Kalman algorithm, this paper proposes a better tracking algorithm for snowboard moving targets. In the method designed in this paper, in order to solve the problem, a multi-algorithm fusion target tracking algorithm is proposed. Firstly, the SIFT feature algorithm is used for rough matching to determine the fuzzy position of the target. Then, the good performance of the mean shift algorithm is used to further match the target position and determine the exact position of the target. Finally, the Kalman filtering algorithm is used to further improve the target tracking algorithm to solve the template trajectory prediction under occlusion and achieve the target trajectory tracking algorithm design of snowboarding. Show more

Keywords: Snowboarding, multi-target matching tracking, occluding target, multi-algorithm fusion

DOI: 10.3233/JIFS-189350

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 2, pp. 3117-3125, 2021

Authors: Lu, Yan’an | Shi, Lei

Article Type: Research Article

Abstract: This research mainly discusses the characteristics of BIM architecture design and its application in traditional residential design from the perspective of smart cities. Given the topics that people are more concerned about, this research mainly uses BIM modeling technology to initially build a virtualized building model. It discusses the convenience of intelligent automation technology in terms of resource consumption and house security. In terms of safety, different levels of wind blowing strength are mainly used to measure the distance moved by the house to evaluate the safety factor. Divide the wind blowing intensity into A, B, C, D, E, F, …and 6 levels to test the strength of the house. When the wind intensity level is F, the safety factor is the weakest, which is 20%. When conducting a house consumption test, directly measure the house’s electricity consumption within a specified time to conduct a resource rate consumption test. Divide the time period into 1 h, 2 h, 3 h, 4 h, 5 h, 6 h, 6 different time periods to measure power consumption. The resource consumption rate reaches a maximum value of 96% when the length of time is 6 h. The experimental results show that the safety characteristics of BIM technology are the weakest when the wind strength level is F, and the safety performance is different when the wind strength level is different. In terms of resource consumption, the resource consumption rate reaches the maximum value when the time is 6 h, and the length of time directly determines the housing resource consumption rate. From the perspective of a smart city, BIM building design has the advantages of low resource consumption and high safety factor. Show more

Keywords: Smart city, BIM architectural design, traditional residential design, safety factor, house strength

DOI: 10.3233/JIFS-189351

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 2, pp. 3127-3136, 2021

Authors: Zhao, Chen | Xue, Ye | Niu, Tong

Article Type: Research Article

Abstract: Nowadays, with the development of science and technology, the progress of society, and the fierce competition among enterprises in the market, the current market competition has gradually turned into the competition of talents, and the excellent talent reserve of enterprises is a competitive advantage. However, there are many enterprises and many places where human resource management is not in place. At the same time, many imperceptible problems in human resource management, most of which are hidden and uncertain, lead to business problems and related phenomena and threaten the further development of enterprises. Although there are many research methods for these …problems, it is difficult to analyze the current situation with this method because of its strong subjectivity. In order to better solve the above problems, this paper studies the standard system of human resource management under the background of the fuzzy system and uses the new structure of human resource fuzzy theory decision-making which has strong theoretical and practical value in human resource system. In the research of this paper, human resource management indicators are divided into comprehensive and professional. Aiming at these two categories of indicators, this paper uses human resource management theory to analyze them systematically and designs a more reasonable indicator system. Then, taking an enterprise as an example, it uses a fuzzy comprehensive evaluation method to combine qualitative and quantitative research to analyze the enterprise. In the analysis, this paper finds that there are some problems in human resource management, such as performance management is not in place, employees’ sense of belonging is not strong, and through the fuzzy comprehensive evaluation of the enterprise situation, it is found that the enterprise human resource management system is good, but still needs to further improve the enterprise management system. Show more

Keywords: Fuzzy theory, human resource management theory, comprehensive evaluation

DOI: 10.3233/JIFS-189352

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 2, pp. 3137-3146, 2021

Authors: Zheng, Xiangyu | Jia, Rong | Aisikaer, | Gong, Linling | Zhang, Guangru | Dang, Jian

Article Type: Research Article

Abstract: Ensuring the stable and safe operation of the power system is an important work of the national power grid companies. The power grid company has established a special power inspection department to troubleshoot transmission line components and replace faulty components in a timely manner. At present, assisted manual inspection by drone inspection has become a trend of power line inspection. Automatically identifying component failures from images of UAV aerial transmission lines is a cutting-edge cross-cutting issue. Based on the above problems, the purpose of this article is to study the component identification and defect detection of transmission lines based on …deep learning. This paper expands the dataset by adjusting the size of the convolution kernel of the CNN model and the rotation transformation of the image. The experimental results show that both methods can effectively improve the effectiveness and reliability of component identification and defect detection in transmission line inspection. The recognition and classification experiments were performed using the images collected by the drone. The experimental results show that the effectiveness and reliability of the deep learning method in the identification and defect detection of high-voltage transmission line components are very high. Faster R-CNN performs component identification and defect detection. The detection can reach a recognition speed of nearly 0.17 s per sheet, the recognition rate of the pressure-equalizing ring can reach 96.8%, and the mAP can reach 93.72%. Show more

Keywords: Power line detection, deep learning, component recognition, faster R-CNN, network model

DOI: 10.3233/JIFS-189353

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 2, pp. 3147-3158, 2021

Authors: Li, Weiguang

Article Type: Research Article

Abstract: With the vigorous promotion of the construction of smart campus by the ministry of education, the development concept of smart campus will have broad application prospects. However, colleges and universities are still at the stage of digital campus and there are many problems left. It is difficult to complete the transition from digital campus to smart campus. The main problem is that the campus data has only been digitized but not informational. The purpose of this article is to study a smart campus management system based on the Internet of Things technology. This research uses the unified data collection source …of face recognition terminal hardware products based on the Internet of Things technology, unified management in the background of the system, and calculates and analyzes the data to obtain valuable campus big data. This study designed and implemented a complete smart campus management system by analyzing the system design principles and design goals. This system is mainly divided into the face recognition terminal hardware and smart campus software system based on the Internet of Things. By analyzing the data generated by students and faculty and staff, it can provide a reference for campus managers to improve management quality, and help teachers and students to formulate more efficient learning and teaching and research plans. This article tests the practicability of the system and obtains the user’s satisfaction as 8.0. Show more

Keywords: Internet of things, smart campus, management system, big data, smart terminal

DOI: 10.3233/JIFS-189354

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 2, pp. 3159-3168, 2021

Authors: Liu, Ying | Wang, Guoshi | Guo, Wei | Zhang, Yingbin | Dong, Weiwei | Guo, Wei | Wang, Yan | Zeng, ZhiXiang

Article Type: Research Article

Abstract: The power grid is the foundation of the development of the national industry. The rational and efficient distribution of power resources plays an important role in economic development. The smart grid is the use of modern network information technology to realize the exchange of data information between grid devices. The construction of smart grids has accumulated a huge amount of data resources. At present, the demand for power companies to “use data management enterprises and use the information to drive services” is increasingly urgent. Power big data has become the basis for grid companies to make decisions, but the accumulation …of pure data does not bring benefits to grid companies. Therefore, making full use of these actual data based on the grid, in-depth analysis, and discovering and using the hidden information is of great significance for guiding the power companies to make correct decisions. This paper first analyzes the differences between smart grids and traditional grids and provides an overview of data mining techniques, including the association rules commonly used in association analysis. Then the application scenarios of data mining in the smart grid are put forward, and data mining technology is applied to power load forecasting. The experimental results show that the data mining method and actual results of the power load forecasting in the smart grid environment proposed in this paper are within a reasonable range. Therefore, the results of load forecasting in this paper are still of practical value. Show more

Keywords: Smart grid, data mining, big data, association rules

DOI: 10.3233/JIFS-189355

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 2, pp. 3169-3175, 2021

Authors: Xindi, Yang | Huanran, Du

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: Data migration, media content, QPop, log mining

DOI: 10.3233/JIFS-189356

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 2, pp. 3177-3184, 2021