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The purpose of the Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology is to foster advancements of knowledge and help disseminate results concerning recent applications and case studies in the areas of fuzzy logic, intelligent systems, and web-based applications among working professionals and professionals in education and research, covering a broad cross-section of technical disciplines.
The journal will publish original articles on current and potential applications, case studies, and education in intelligent systems, fuzzy systems, and web-based systems for engineering and other technical fields in science and technology. The journal focuses on the disciplines of computer science, electrical engineering, manufacturing engineering, industrial engineering, chemical engineering, mechanical engineering, civil engineering, engineering management, bioengineering, and biomedical engineering. The scope of the journal also includes developing technologies in mathematics, operations research, technology management, the hard and soft sciences, and technical, social and environmental issues.
Authors: Chen, Tao | Lv, Hongxia | Sun, Yichen | Wang, Xiaoyi
Article Type: Research Article
Abstract: As one kind of highest hierarchy node on the network, the transfer scheme of high-speed railway hub timetable should be studied at priority. After defining the problem that optimizing transfer scheme of timetable at high-speed railway hub, this paper proposes time adjusting strategy and platform adjusting strategy to optimize the problem, of which the first strategy introduces a FUZZY set of reasonable time range to reduce the possible train conflicts at adjacent stations on the network, and the second strategy helps to use different transfer time to match the arrival and departure of trains. Then, an optimization model of timetable …based on passenger transfer is established with the minimized invalid transfer waiting time for passenger and train conflicts at adjacent stations as the objective function. The model is solved by the above two strategies in MATLAB software. Finally, the rationality and effectiveness of this model are verified, taking Shanghai Hongqiao Station as an example. Show more
Keywords: High-speed railway, hub, transfer, timetable optimization
DOI: 10.3233/JIFS-179662
Citation: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 5, pp. 5743-5752, 2020
Authors: Xu, Changan | Li, Sihan | Xu, Heying | Ni, Shaoquan
Article Type: Research Article
Abstract: Passenger train occupation rate directly affects Railway Company’s revenue and capacity utilization of railway infrastructure, and measures to improve passenger train occupation rate is always the focus of railway companies’ attention. However, researches on what, and how factors influence passenger train occupation rate remain sparse. Based on the collective data of 363 passenger trains on the Beijing-Shanghai High-speed Railway in November 2015, this paper establishes a data-driven analysis framework to explore the influencing factors of passenger train occupation rate. Specifically, we first analyze the possible factors that influence train occupation rate from the perspective of train service planning. Then, the …approach of association rules is applied to analyze the potential relationship between train occupation rate and its influencing factors. And a total of 6711 and 8133 association rules were generated for high and low train occupation rate of passenger trains, respectively. Further analysis found that train departure and arrival times, train departure and arrival station class and the type of trains are the main factors influencing the level of train occupation rate. These findings can provide reference for train service planning. Show more
Keywords: Passenger train occupation rate, association rules, train service planning, Beijing-Shanghai high-speed railway
DOI: 10.3233/JIFS-179663
Citation: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 5, pp. 5753-5761, 2020
Authors: Yang, Tingyu | Peng, Xiaoqian | Chen, Dingjun | Yang, Feiyu | Muneeb Abid, Malik
Article Type: Research Article
Abstract: With the increasingly close links between provinces and municipalities, the complexity and social connectivity of emergencies have gradually increased. How to realize the rapid and scientific dispatch of emergency resources based on the comprehensive transportation network has become a realistic need. However, due to barriers in management and communication between different administrative regions and different modes of transportation, emergency resource scheduling can only be carried out in the region, and the utilization of integrated traffic channels is insufficient to form a good multimodal transport system. The multi-agent system has strong self-organization ability, learning ability and reasoning ability, which solves problems …in the fields of dynamic decision-making and micro-simulation and provides ideas for solving the problem of comprehensive traffic emergency dispatching across regions. In this paper, the multi-agent system is introduced into the research of the task assignment problem of trans-regional comprehensive traffic emergency materials dispatching, based on the traditional bidding rules, the emergency dispatch task assignment rules are proposed and multi-agent trans-regional comprehensive traffic emergency dispatching model based on improved bidding rules is established. The simulation results show that the proposed method can break the regional barrier and form a multimodal transport scheme for emergency materials from the reserve point to the demand point under the minimum generalized time cost, providing decision support for emergency dispatch. Show more
Keywords: Multi-agent, trans-region, emergency dispatch, bidding
DOI: 10.3233/JIFS-179664
Citation: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 5, pp. 5763-5774, 2020
Authors: Pan, Jeng-Shyang | Yang, Cheng | Meng, Fanjia | Chen, Yuxin | Meng, Zhenyu
Article Type: Research Article
Abstract: Differential Evolution (DE) algorithm generates a population of individuals by encoding with a floating point vector, and it is a simple and effective population-based stochastic optimization algorithm for global optimization of continuous space. Because of its excellent performance, DE variants can be applied in a wide range of applications in science and engineering. However, the performance of DE is sensitive to the choice of trial vector generation strategy and the associated control parameters. Therefore, it is necessary to choose appropriate mutation strategy and control parameters when tackling optimization applications. In this paper, an adaptive update mechanism is proposed to update …control parameters F and Cr . The experimental results are verified on the CEC 2013 test suite which contains 28 benchmark functions for the evaluation of single objective real parameter optimization. The proposed algorithm is compared with jDE, iwPSO and ccPSO, and experiment results show its good performance. Show more
Keywords: Adaptive update mechanism, differential evolution, real parameter optimization, stochastic optimization
DOI: 10.3233/JIFS-179665
Citation: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 5, pp. 5775-5786, 2020
Authors: Wu, Tsu-Yang | Lin, Jerry Chun-Wei | Yun, Unil | Chen, Chun-Hao | Srivastava, Gautam | Lv, Xianbiao
Article Type: Research Article
Abstract: Association-rule mining (ARM) has concerned as an important and critical research issue in the field of data analytics and mining that aims at finding the correlations among the items in binary databases. However, the conventional algorithms considered the frequency of the item(set) in binary databases for ARM, which is not sufficient in real-life situations. Mining of useful information is not an easy task especially if the item(set) consists of the added values. Moreover, the discovered knowledge is not easy to understand if you are not the domain experts. For the past decades, several intelligent systems involved the fuzzy-set theory for …many domains and applications due to it is interpretable for human reasoning. Before, the Apriori-based method for discovering fuzzy frequent itemsets (FFIs) based on the type-2 fuzzy-set theory was proposed, which requires the amount of computations with enormous candidates. In this study, we then first present a fast list-based multiple fuzzy frequent itemset mining (named as LFFT2)algorithm under type-2 fuzzy-set theory. It is developed by the type-2 membership functions to retrieve the multiple fuzzy frequent itemsets for presenting more useful and meaningful knowledge for making the efficient strategies or decisions. From the results shown in the experiments, it is clear to see that the developed LFFT2 outperforms the conventional Apriori-based approach regarding the execution time and the number of examined nodes in the search space. Show more
Keywords: Data mining, fuzzy frequent itemset mining, type-2 fuzzy-set theory, list-based structure
DOI: 10.3233/JIFS-179666
Citation: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 5, pp. 5787-5797, 2020
Authors: Lisang, Liu | Dongwei, He | Jishi, Zheng | Ying, Ma | Jing, Huang | Junfeng, Fan | Xiaoyu, Wei | Jinxin, Yao
Article Type: Research Article
Abstract: The intelligent tracking car can realize self-perception, behavioral decision-making, automatic driving, etc. for environmental information, and has a wide application in our lives. In this paper, a new intelligent car is designed based on STM32F407ZGT6 MCU. The track information is collected by the OV7725 camera. The fast OTSU adaptive threshold algorithm is used to obtain the path guiding center line, which can realize image collection, image analysis and sensor data fusion, blocked path identification and intelligent judgment, automatic tracking function. The test results show that the algorithm is effective and feasible. When there are obstacles or partial loss on the …track, it can intelligently identify the effective and obstacles and realize the independent decision making. It has good dynamic and robustness. Show more
Keywords: Machine vision, intelligent car, tracking, obstacle avoidance
DOI: 10.3233/JIFS-179667
Citation: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 5, pp. 5799-5810, 2020
Authors: Nguyen, Trong-The | Qiao, Yu | Pan, Jeng-Shyang | Chu, Shu-Chuan | Chang, Kuo-Chi | Xue, Xingsi | Dao, Thi-Kien
Article Type: Research Article
Abstract: Metaheuristic algorithms have been applied widely for real-world problems in many fields, e.g., engineering, financial, healthcare. Bats algorithm (BA) is a recent metaheuristic algorithm with considering as a robust optimization method that can outperform existing algorithms. However, when dealing with complicated combinatorial problems such as traveling salesman problems (TSP), the BA can be fallen in a local optimum. This paper proposes a new hybridizing Parallel BA (HPBA) with a mutation in local-search to escape such its drawback scenario for TSP. A graph theory mutation method is used to embed for hybridizing BA with exploiting similarities among individuals. The proposed method …is extensively evaluated in TSP with series instances of the benchmark from TSPLIB to test its performance. The compared experimental result with the previous method and the best-known solutions (B.K.S) in the literature shows that the proposed approach offers competitive results. Show more
Keywords: Transportation applications, metaheuristic algorithms, hybridized parallel bats algorithm
DOI: 10.3233/JIFS-179668
Citation: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 5, pp. 5811-5820, 2020
Authors: Zhang, Xiaoqing | Zheng, Yongguo | Liu, Weike | Peng, Yanjun | Wang, Zhiyong
Article Type: Research Article
Abstract: Accurate extraction of urban buildings is a key problem in urban remote sensing image processing. It can be applied to many kinds of urban problems, such as data statistics of urban management and smart cities. In recent years, the deep learning model based on convolutional neural network is widely used in the field of target recognition and semantic segmentation. In this paper, based on U-Net for urban building extraction from remote sensing image, we propose a neural network architecture for urban building extraction from remote sensing image. We use depth separable convolution to improve it and adjust the process of …network super parametric optimization according to the characteristics of building. We call this new architecture XU-Net. We evaluate the performance of XU-Net through experiments with INRIA aerial image data set. The result shows that XU-Net is not only feasible but also efficient. Moreover, XU-Net reduces number of parameters 89%, from 18.8M to 2.13M, compared to classical architecture U-Net, at the same time, it guarantees the accuracy can reach 97.5%. Show more
Keywords: U-net, depthwise separable convolution, semantic segmentation, urban building extraction
DOI: 10.3233/JIFS-179669
Citation: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 5, pp. 5821-5829, 2020
Authors: Wu, Jimmy Ming-Tai | Teng, Qian | Lin, Jerry Chun-Wei | Yun, Unil | Chen, Hsing-Chung
Article Type: Research Article
Abstract: HAUIM (High Average-Utility Itemset Mining) is a variation of HUIM (High-Utility Itemset Mining) that provides a reliable measure to reveal utility patterns in light of the length of the mined pattern. Several works have been studied to improve mining efficiency by designing multiple pruning strategies and efficient frameworks, but fewer studies have centered on the sophisticated database maintenance algorithm. Existing works still have to rescan the databases multiple times when it is necessary. We first use the pre-large principle in this paper to efficiently update the newly discovered HAUIs. For further updates and maintenance on the basis of the two …thresholds, the Pre-large Average Utility Itemset (PAUI) can be maintained to increase the mining performance. Experiments will then be performed to compare the batch model, the Fast-Updated (FUP)-based model, and the Apriori-like HAUIM (APHAUIM) model designed in respect of the number of maintenance patterns, scalability, runtime, and memory usage. Show more
Keywords: pre-large, high average-utility itemset mining, dynamic database, incremental, transaction insertion
DOI: 10.3233/JIFS-179670
Citation: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 5, pp. 5831-5840, 2020
Authors: Kiss, Gabor
Article Type: Research Article
Abstract: The expectation of spreading autonomous vehicles lies in the hope of significantly decreasing the 1,3 million death toll accidents worldwide, which are caused by human factor 90% of the time. In policies of insurance companies the reaction time of a human realizing any dangerous situation, reacting to it and putting the breaks into action is two seconds. The reaction time would be reduced by the power of AI that can process the huge amount of data coming from sensors and with the information regarding the situation could make decision much faster than men. The aim of the research is to …denote several situations and possibilities that are capable of deceiving, diverting, capturing a self-driving car or even turning it against the other vehicles by influencing the decision-making of the artificial intelligence. In this paper I will discuss several situations that might be able to confuse the artificial intelligence of the autonomous vehicles or to make them come to an inadequate decision. You can see that safe decision-making depends on the teaching method of the artificial intelligence as well as the correctness of the data uploaded. The other aim of the research is to demonstrate how could work a Manchurian Artificial Intelligence in autonomous vehicles. I will introduce the idea of Manchurian artificial intelligence which can be activated by a certain event and can pose a threat to the passengers of the vehicles. If it is present in the software of several vehicles, a chain of worldwide accidents can be induced at a certain time. Show more
Keywords: Manchurian AI, self-driving car, autonomous vehicle, external manipulation
DOI: 10.3233/JIFS-179671
Citation: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 5, pp. 5841-5845, 2020
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