{"title":"An ANFIS Based Derivations of Inference Rules for Users’ Adoptions of Autonomous Vehicles","authors":"Chi-Yo Huang, Yun Lin, Yu-Feng Lu, Liang-Chieh Wang, Ying-Ting Kuo, Jeng-Chieh Cheng, Yu Sun","doi":"10.1109/iFUZZY50310.2020.9297811","DOIUrl":"https://doi.org/10.1109/iFUZZY50310.2020.9297811","url":null,"abstract":"Autonomous Vehicles (AVs) have great potential and can improve transportation efficiency and safety through minimal manual intervention and optimized traffic control systems. Advances in artificial intelligence and real-time data processing technology have promoted the development of practical AVs. AV manufacturers are trying to understand the potential factors that may affect consumers' acceptance of autonomous vehicles. However, there is very little research on autonomous vehicles and consumers. In order to understand these factors, this research will use UTAUT 2, as a research framework to predict consumer intentions and behaviors. This research will first review the literature, invite experts to define and evaluate appropriate criteria and dimensions, and use the ANFIS is used to derive the decision rules, and the weights of the corresponding rules are compared. The resulting analysis can be used as a basis for predicting consumer acceptance of AVs in the future.","PeriodicalId":215352,"journal":{"name":"2020 International Conference on Fuzzy Theory and Its Applications (iFUZZY)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131101082","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Interval Type 2 Fuzzy Analytic Hierarchy Process Synthesizing with Ordered Weighted Average Variation of Bonferroni Mean Operator","authors":"Kuo-Ping Chiao","doi":"10.1109/iFUZZY50310.2020.9297366","DOIUrl":"https://doi.org/10.1109/iFUZZY50310.2020.9297366","url":null,"abstract":"In multiple criteria decision making (MCDM), analytic hierarchy process (AHP) is one of the widely used methodologies. The synthesis of the local weighted rates to the global rates is a critical stage. AHP assumes that the decision criteria are independent. However, most real MCDM problems involve the set of criteria that are interrelated each other. Bonferroni mean (BM) can express the interrelationship of the input arguments. The BM is a mean type aggregator in decision making with different combinations of indexes. In this paper, based on Yager's ordered weighted average (OWA), the crisp BM operator is extended to the models with interval type 2 fuzzy sets (IT2FS) decision input judgments. The IT2FS aggregation models with BM OWA weights and linguistic quantifier guided OWA weights associated with orness levels are developed. The traditional AHP is extended with the developed IT2FS OWA variation of BM aggregation models in the AHP synthesizing stage. Such IT2FS AHP models can deal with even more realistic decision making problems. A warehouse location MCDM problem with interrelated attributes is examined for illustrating the proposed IT2FS AHP synthesis models.","PeriodicalId":215352,"journal":{"name":"2020 International Conference on Fuzzy Theory and Its Applications (iFUZZY)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133205001","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Artificial Bee Colony with Mutual Search Strategy and Search Mode Control","authors":"Sheng-Ta Hsieh, Chun-Ling Lin, Zhao-Wei Wang","doi":"10.1109/iFUZZY50310.2020.9297365","DOIUrl":"https://doi.org/10.1109/iFUZZY50310.2020.9297365","url":null,"abstract":"The artificial bee colony (ABC) was inspired by bees’ foraging behavior. Bees of the colony will try to find better food source (potential solutions) in solution space. After multiple iterations, the bees in the colony may move closer as a few clusters even are trapped in local optimum. In this paper, the search mode control is proposed; the bees will explore or exploit solution space for finding better solutions. Further, the mutual search strategy is proposed to guide bees move to potential food source. The bees will provide various and useful information to each other for searching potential solutions. In experiments, 10 test functions of CEC 2019 are adopted to test proposed method and compare to related works. The proposed method not only can improve original ABC but also perform better than another ABC variant.","PeriodicalId":215352,"journal":{"name":"2020 International Conference on Fuzzy Theory and Its Applications (iFUZZY)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124977773","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Using Interval Type-2 Recurrent Fuzzy Cerebellar Model Articulation Controller Based on Improved Differential Evolution for Cooperative Carrying Controller of Mobile Robots","authors":"Tzu-Chao Lin, Chao-Chun Chen, Cheng‐Jian Lin","doi":"10.1109/iFUZZY50310.2020.9297367","DOIUrl":"https://doi.org/10.1109/iFUZZY50310.2020.9297367","url":null,"abstract":"Mobile robot is widely utilized in various fields such as navigation control, obstacle avoidance and object carrying. For keeping away from obstacles to avoid collision and preventing object carrying from dropping down, we propose a state manager (SM) designed to assist the mobile robots so that they can switch operation between wall-following carrying (WFC) and toward goal carrying (TGC) by different external condition. In this controlling model, interval type-2 recurrent fuzzy cerebellar model articulation controller (IT2RFCMAC), embedded with a modified evolutionary optimization and dynamic grouping differential evolution (DGDE), is implemented for WFC and TGC. By adopting reinforcement learning strategy, mobile robots equip with adaptively wall-following control to make cooperative carrying control in real.","PeriodicalId":215352,"journal":{"name":"2020 International Conference on Fuzzy Theory and Its Applications (iFUZZY)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131433986","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Deep Learning for Improving Image Quality with Uneven Illumination Images","authors":"Cheng-Ta Chuang, Zih-Syuan Jhan","doi":"10.1109/iFUZZY50310.2020.9297362","DOIUrl":"https://doi.org/10.1109/iFUZZY50310.2020.9297362","url":null,"abstract":"There are many mobile scanning apps available on the market today that you can download onto your smartphone. HP Smart, Microsoft Office Lens and Adobe Scanner are the most popular document scanning apps. These offer the convenience of converting printed text into digital text available for edits, copy and storage in any digital device. Uneven lighting is one of the leading disturbance sources that can affect the scanning result. Therefore, this paper aims to realize the scanning function. It improves the image quality by removing the noise using deep neural network. Compared with the existing Adobe Scan, our method performs better in presence of uneven lighting.","PeriodicalId":215352,"journal":{"name":"2020 International Conference on Fuzzy Theory and Its Applications (iFUZZY)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121781694","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Development of the Autonomous Battery Replacement System on the Unmanned Ground Vehicle for the Drone Endurance","authors":"Chien-Wu Lan, Cheng-Ju Wu, Huai-Jie Shen, Hua-Chien Lin, Po-Jui Chu, Chun-Fei Hsu","doi":"10.1109/iFUZZY50310.2020.9297363","DOIUrl":"https://doi.org/10.1109/iFUZZY50310.2020.9297363","url":null,"abstract":"The purpose of this research is to develop an unmanned ground vehicle (UGV) with an autonomous battery replacement system (BRS) to realize the drone endurance by replacing a backup power. When the power of a drone is about to run out, the unmanned ground vehicle will be controlled to go to a position near the drone to wait the drone lands on the UGV. Since an ArUco marker is designed on the UGV, the UGV can be located by detecting the ArUco marker, and assists for the drone landing. After the drone lands on the UAV, the battery replacement system will start the battery replacement program automatically. After the battery is replaced, the drone can continue to perform the mission to achieve the purpose of the endurance flight.","PeriodicalId":215352,"journal":{"name":"2020 International Conference on Fuzzy Theory and Its Applications (iFUZZY)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128144190","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Study on Fast Charging Method of Series Connected Lithium-Ion Battery Strings with Intelligent Control","authors":"Ching-Chun Chuang, Chun-Jen Yao, Sen-Tung Wu","doi":"10.1109/iFUZZY50310.2020.9297813","DOIUrl":"https://doi.org/10.1109/iFUZZY50310.2020.9297813","url":null,"abstract":"The unbalance phenomenon of lithium-ion batteries undercharging and the discharging condition is presented. Constant current and constant voltage controller and fuzzy controller are designed and simulated to evaluate the charging time for series-connected lithium-ion batteries. The charging methods are all evaluated and verified in the MATLAB/SIMULINK environment. The CC-CV controller and fuzzy controller are used to adjusting the charging current for series-connected lithium-ion batteries. The proposed method not only decreases the battery temperature but also improves the performance of the charging in the lithium-ion the battery. Eventually, To study the fast charging methods for minimizing battery temperature rising is important to extend the life cycle of the battery.","PeriodicalId":215352,"journal":{"name":"2020 International Conference on Fuzzy Theory and Its Applications (iFUZZY)","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130116313","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Adaptive Model Predictive Control Using Iterative Fuzzy Broad Learning System for Nonlinear Digital Time-Delay Dynamic Systems","authors":"Hung-Sheng Chen, Ching-Chih Tsai, Feng-Chun Tai","doi":"10.1109/iFUZZY50310.2020.9297812","DOIUrl":"https://doi.org/10.1109/iFUZZY50310.2020.9297812","url":null,"abstract":"This paper presents a new learning control structure using fuzzy broad learning system (FBLS) for adaptive model predictive control (AMPC) of nonlinear digital time-delay dynamic systems. The proposed control method, abbreviated as FBLS-ANMPC, is novel in combining FBLS and model predictive control to develop a FBLS-ANMPC control law for high-performance setpoint tracking control and disturbance rejection. Comparative simulations are well used to demonstrate the effectiveness and merits of the proposed method in comparison with five existing methods. Experimental results on temperature control of a heating barrel in a plastic injection molding machine are conducted to show the practicability of the proposed method.","PeriodicalId":215352,"journal":{"name":"2020 International Conference on Fuzzy Theory and Its Applications (iFUZZY)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134264975","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Using Computer-Generated Examples to Support Idea Generation","authors":"Yi-Jheng Huang, Wen-Chieh Lin, Suiang-Shyan Lee, Xun-Yi Huang","doi":"10.1109/iFUZZY50310.2020.9297808","DOIUrl":"https://doi.org/10.1109/iFUZZY50310.2020.9297808","url":null,"abstract":"We present ComposIt, a creativity support tool that assists designers in finding inspiration by providing many computer-generated examples. These examples may be beyond humans’ imagination and thus are helpful to inspire users to create new ideas. To automatically produce examples, our system adopts the deconstruction and construction strategies that are commonly used in the creative industries. Given a 3D model, the model deconstruction module analyzes the model and divides it into several elements. Then the model construction module synthesizes examples by composing the elements from different models. To evaluate the effectiveness of our system, we conducted a user study, in which artists were invited to design using our system. The results conclude that our system is able to inspire artists in their design process. The artists also shared their usage experience of our system in various aspects.","PeriodicalId":215352,"journal":{"name":"2020 International Conference on Fuzzy Theory and Its Applications (iFUZZY)","volume":"222 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114405104","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Performance of Q-learning Algorithms for Channel Allocation in Small Cell Networks","authors":"Yung-Fa Huang, Shing-Hong Liu, Tan-Hsu Tan, Li-Chun Hou","doi":"10.1109/iFUZZY50310.2020.9297810","DOIUrl":"https://doi.org/10.1109/iFUZZY50310.2020.9297810","url":null,"abstract":"The small cell networks (SCNs) architecture can greatly increase data capacity. After LTE-A (Long Term Evolution-Advance), the SCN has become the main architecture of the Fifth Generation (5G) communication systems. In SCN, the increasing interference between adjacent base stations can be effectively controlled through an adaptive channel allocation. Therefore, this paper investigates the adaptive channel allocation of small cell networks by using Q-learning via ε-greedy exploration strategy and Softmax exploration strategy. Simulation results show that the Softmax-LC (Logarithmic Cooling) discovery strategy can obtain throughput of 52 Mbps at 70 time steps, while the Exponential ε-greedy strategy obtains 52 Mbps at 200 time steps.","PeriodicalId":215352,"journal":{"name":"2020 International Conference on Fuzzy Theory and Its Applications (iFUZZY)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125584143","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}