Pub Date : 2022-09-09DOI: 10.1109/ICMLC56445.2022.9941284
K. Mori, Y. Tange
In this study, we developed the model predicted the deep temperatures from the surface temperature information in order to realize non-invasive measurement for the hyperthermia therapy. The deep temperatures were predicted based on the surface temperature, surface temperature change, initial surface temperature, and lapsed time by using deep learning method based on long short term memory. The model was learned by using temperature characteristics measured by biological phantoms composed by agar. Errors of the model’s prediction accuracies for the phantoms were around 0.45 degree at the largest point. We measured the temperature characteristics of the pork-based phantom as a material similar to human tissue and used the model to make predictions. Errors of the prediction accuracies for the phantom were around 5.0 degree at the largest point. In this study, we used two type heat sources. The model does not enough learn temperature characteristics for each heat source. We confirmed that the system was able to achieve a prediction accuracy of less than 0.3 degree for data using a heat pack as a heat source
{"title":"Non-Invasive Deep Temperature Measurement Based on the Long Short Term Memory for Hyperthermia Therapy","authors":"K. Mori, Y. Tange","doi":"10.1109/ICMLC56445.2022.9941284","DOIUrl":"https://doi.org/10.1109/ICMLC56445.2022.9941284","url":null,"abstract":"In this study, we developed the model predicted the deep temperatures from the surface temperature information in order to realize non-invasive measurement for the hyperthermia therapy. The deep temperatures were predicted based on the surface temperature, surface temperature change, initial surface temperature, and lapsed time by using deep learning method based on long short term memory. The model was learned by using temperature characteristics measured by biological phantoms composed by agar. Errors of the model’s prediction accuracies for the phantoms were around 0.45 degree at the largest point. We measured the temperature characteristics of the pork-based phantom as a material similar to human tissue and used the model to make predictions. Errors of the prediction accuracies for the phantom were around 5.0 degree at the largest point. In this study, we used two type heat sources. The model does not enough learn temperature characteristics for each heat source. We confirmed that the system was able to achieve a prediction accuracy of less than 0.3 degree for data using a heat pack as a heat source","PeriodicalId":117829,"journal":{"name":"2022 International Conference on Machine Learning and Cybernetics (ICMLC)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131766725","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}
Pub Date : 2022-09-09DOI: 10.1109/ICMLC56445.2022.9941286
Meng-Luen Wu, Chen Lin, Po-Cheng Yu
Recent years, computer-aided penalty prediction have been promoted to gain people's trust to the judicial systems, especially in developing Chinese region. In this paper, we propose machine learning based models to predict the legal penalty of criminal cases. Particularly, we focus on drunk driving cases as they are frequent, and the regulations are clear. Unlike western text which words are separated by spaces, words in Chinese text are continuum. In our proposed method, we first use a word segmentation method to separate the Chinese words in text and apply a pre-trained model to convert words into vectors. In the vector space, words with similar meanings have short distance with each other. As the amount of each penalty varies greatly, resulting a data imbalance problem. Therefore, we adapt the Synthetic Minority Oversampling Technique (SMOTE) algorithm as a solution. Finally, we apply deep learning-based models, including Bi-GRU and TextCNN to perform penalty prediction, and compare their advantages and disadvantages.In the experimental result, for drunk driving case penalty prediction, our propose SMOTE + TextCNN solution can reach 73.96% of accuracy. If we allow the prediction to be plus or minus one month from the actual, the accuracy is 95.60%. As for the computation time, our proposed method can predict the penalty of 1,524 drunk driving cases per second.
{"title":"On The Development of a Legal Penalty Prediction System for Drunk Driving Cases","authors":"Meng-Luen Wu, Chen Lin, Po-Cheng Yu","doi":"10.1109/ICMLC56445.2022.9941286","DOIUrl":"https://doi.org/10.1109/ICMLC56445.2022.9941286","url":null,"abstract":"Recent years, computer-aided penalty prediction have been promoted to gain people's trust to the judicial systems, especially in developing Chinese region. In this paper, we propose machine learning based models to predict the legal penalty of criminal cases. Particularly, we focus on drunk driving cases as they are frequent, and the regulations are clear. Unlike western text which words are separated by spaces, words in Chinese text are continuum. In our proposed method, we first use a word segmentation method to separate the Chinese words in text and apply a pre-trained model to convert words into vectors. In the vector space, words with similar meanings have short distance with each other. As the amount of each penalty varies greatly, resulting a data imbalance problem. Therefore, we adapt the Synthetic Minority Oversampling Technique (SMOTE) algorithm as a solution. Finally, we apply deep learning-based models, including Bi-GRU and TextCNN to perform penalty prediction, and compare their advantages and disadvantages.In the experimental result, for drunk driving case penalty prediction, our propose SMOTE + TextCNN solution can reach 73.96% of accuracy. If we allow the prediction to be plus or minus one month from the actual, the accuracy is 95.60%. As for the computation time, our proposed method can predict the penalty of 1,524 drunk driving cases per second.","PeriodicalId":117829,"journal":{"name":"2022 International Conference on Machine Learning and Cybernetics (ICMLC)","volume":"7 9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133939360","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}
Pub Date : 2022-09-09DOI: 10.1109/ICMLC56445.2022.9941285
Kensuke Shigenaga, K. Nagamune
The purpose of this study was to evaluate the effectiveness of the VR Kohs Block Design Test and the relationship between eye movements and hand movements by reproducing the Kohs Block Design Test in a VR space and measuring the subjects’ eye and hand movements during the test.Using the developed system, we conducted the actual Kohs Block Design Test and the Kohs Block Design Test on VR with three healthy adult male subjects.As a result, it was found that the current VR Kohs Block Design Test is very difficult to perform grasping movements, and that it is necessary to construct a highly realistic system. The subject’s gaze and hand movements during the test were generally consistent, indicating that the subject was simultaneously performing grasping and gazing.
{"title":"A Development of Kohs Block Design Test in Virtual Reality with Eye Tracking and Hand Tracking","authors":"Kensuke Shigenaga, K. Nagamune","doi":"10.1109/ICMLC56445.2022.9941285","DOIUrl":"https://doi.org/10.1109/ICMLC56445.2022.9941285","url":null,"abstract":"The purpose of this study was to evaluate the effectiveness of the VR Kohs Block Design Test and the relationship between eye movements and hand movements by reproducing the Kohs Block Design Test in a VR space and measuring the subjects’ eye and hand movements during the test.Using the developed system, we conducted the actual Kohs Block Design Test and the Kohs Block Design Test on VR with three healthy adult male subjects.As a result, it was found that the current VR Kohs Block Design Test is very difficult to perform grasping movements, and that it is necessary to construct a highly realistic system. The subject’s gaze and hand movements during the test were generally consistent, indicating that the subject was simultaneously performing grasping and gazing.","PeriodicalId":117829,"journal":{"name":"2022 International Conference on Machine Learning and Cybernetics (ICMLC)","volume":"142 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128066118","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}
Pub Date : 2022-09-09DOI: 10.1109/ICMLC56445.2022.9941300
N. Yagi, Yutaka Hata, Y. Sakai
Since the structure of speech is wide-ranging such as prosody, articulation, vocalization, and breathing, there is no screening test for speech disorder unlike the areas of aphasia and dysphagia. Speech intelligibility in speech-language pathology is evaluated by a Speech-Language-Hearing Therapist (ST), however the evaluation time per person is long and the evaluation criteria are ambiguous. So, the evaluation results will differ depending on the ST. Therefore, in this study, we proposed a system to easily inspect the normality of pronunciation by using 8 characteristics of data divided into single notes. As the results, this system enabled to identify whether the pronunciation is normal or abnormal with high accuracy of 93.3 %.
{"title":"Investigation of Inspection Methods in Acoustic Analysis Using Pronunciation Feature Extraction","authors":"N. Yagi, Yutaka Hata, Y. Sakai","doi":"10.1109/ICMLC56445.2022.9941300","DOIUrl":"https://doi.org/10.1109/ICMLC56445.2022.9941300","url":null,"abstract":"Since the structure of speech is wide-ranging such as prosody, articulation, vocalization, and breathing, there is no screening test for speech disorder unlike the areas of aphasia and dysphagia. Speech intelligibility in speech-language pathology is evaluated by a Speech-Language-Hearing Therapist (ST), however the evaluation time per person is long and the evaluation criteria are ambiguous. So, the evaluation results will differ depending on the ST. Therefore, in this study, we proposed a system to easily inspect the normality of pronunciation by using 8 characteristics of data divided into single notes. As the results, this system enabled to identify whether the pronunciation is normal or abnormal with high accuracy of 93.3 %.","PeriodicalId":117829,"journal":{"name":"2022 International Conference on Machine Learning and Cybernetics (ICMLC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122640232","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}
Pub Date : 2022-09-09DOI: 10.1109/ICMLC56445.2022.9941313
Rung-Ching Chen, Yong-Cun Zhuang, Jeang-Kuo Chen, Christine Dewi
One of the most important responsibilities of a visual driver aid system is recognizing and tracking road signs. In recent years, tremendous progress has been made in both deep learning and the identification of road markings. Pedestrian crossings, directional arrows, zebra crossings, speed limit signs, and similar signs and text are all road surface markings. These markings are painted directly onto the surface of the road. This paper implements YOLOv5s and YOLOv5m to identify the road marking sign. We built a dataset and focused on the Taiwan road marking sign. According to the findings of our experiments, YOLOv5m contains eleven categories of whose training accuracy is superior to that of YOLOv5s. It has been discovered that the YOLOv5m model is the most accurate, scoring 87.30 percent overall throughout testing, while the YOLOv5s model scores an average of 83.60 percent.
{"title":"Deep Learning for Automatic Road Marking Detection with Yolov5","authors":"Rung-Ching Chen, Yong-Cun Zhuang, Jeang-Kuo Chen, Christine Dewi","doi":"10.1109/ICMLC56445.2022.9941313","DOIUrl":"https://doi.org/10.1109/ICMLC56445.2022.9941313","url":null,"abstract":"One of the most important responsibilities of a visual driver aid system is recognizing and tracking road signs. In recent years, tremendous progress has been made in both deep learning and the identification of road markings. Pedestrian crossings, directional arrows, zebra crossings, speed limit signs, and similar signs and text are all road surface markings. These markings are painted directly onto the surface of the road. This paper implements YOLOv5s and YOLOv5m to identify the road marking sign. We built a dataset and focused on the Taiwan road marking sign. According to the findings of our experiments, YOLOv5m contains eleven categories of whose training accuracy is superior to that of YOLOv5s. It has been discovered that the YOLOv5m model is the most accurate, scoring 87.30 percent overall throughout testing, while the YOLOv5s model scores an average of 83.60 percent.","PeriodicalId":117829,"journal":{"name":"2022 International Conference on Machine Learning and Cybernetics (ICMLC)","volume":"2018 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123206079","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}
Pub Date : 2022-09-09DOI: 10.1109/ICMLC56445.2022.9941339
Yudai Ishikawa, K. Tagawa, Hideaki Touyama
This paper proposes a new method of translational manipulation for redirected walking through pitch-oriented viewpoint manipulation, which is known to change the walking speed of a user. Pitch viewpoint manipulation adds a slope to the virtual reality environment. In reality, walking on a slope increases or decreases the walking speed, and this study conducts an investigation based on the assumption that similar fluctuations would occur in a virtual reality environment. Through an experiment, the variation in walking speed by dynamically manipulating the viewpoint in the pitch direction for a 5 m walking section, and the perception threshold, which is the range in which the viewpoint can be manipulated without being noticed by the user, were investigated. The results showed that the walking speed significantly decreased with pitch gains of -0.5° in the downward direction, and 3° and 5° in the upward direction. It was discovered that perceptual thresholds of 0.17° and -1.12° in the upward and downward directions, respectively, were imperceptible, indicating that the viewpoint could be manipulated without being perceived.
{"title":"Alternative Methods of Translational Gains by Viewpoint Manipulation in the Pitch Direction","authors":"Yudai Ishikawa, K. Tagawa, Hideaki Touyama","doi":"10.1109/ICMLC56445.2022.9941339","DOIUrl":"https://doi.org/10.1109/ICMLC56445.2022.9941339","url":null,"abstract":"This paper proposes a new method of translational manipulation for redirected walking through pitch-oriented viewpoint manipulation, which is known to change the walking speed of a user. Pitch viewpoint manipulation adds a slope to the virtual reality environment. In reality, walking on a slope increases or decreases the walking speed, and this study conducts an investigation based on the assumption that similar fluctuations would occur in a virtual reality environment. Through an experiment, the variation in walking speed by dynamically manipulating the viewpoint in the pitch direction for a 5 m walking section, and the perception threshold, which is the range in which the viewpoint can be manipulated without being noticed by the user, were investigated. The results showed that the walking speed significantly decreased with pitch gains of -0.5° in the downward direction, and 3° and 5° in the upward direction. It was discovered that perceptual thresholds of 0.17° and -1.12° in the upward and downward directions, respectively, were imperceptible, indicating that the viewpoint could be manipulated without being perceived.","PeriodicalId":117829,"journal":{"name":"2022 International Conference on Machine Learning and Cybernetics (ICMLC)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116293886","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}
Pub Date : 2022-09-09DOI: 10.1109/ICMLC56445.2022.9941292
Yuxin Ding, Huang Ningxin, Wenting Xu
Currently VANETs still face many serious security issues. One of which is attacks from worms. To prevent the propagation of worms, different immune strategies have been proposed. One problem with these strategies is that they adopt a greedy strategy or random strategy to select immune nodes. These strategies do not consider the dynamic changes of the network topology caused by vehicle movement, which means that the strategies cannot effectively prevent a worm from spreading. In this paper, we propose a dynamic immune strategy. Considering the dynamic changes of VANETs, we use machine learning methods to predict vehicle positions at the next moment and combine the position information of vehicles at different times to evaluate the influence of a vehicle. We provide a method for computing the influence of vehicles. The vehicles with a large influence are selected as immune nodes. We compare the proposed immune strategy with several typical strategies, preemptive immunization, interactive immunization, blacklist isolation and degree immunization. The results show that the proposed method can prevent the spread of worms more effectively than existing techniques.
{"title":"A Dynamic Immune Strategy for Blocking the Spreading of Worms in Vanets","authors":"Yuxin Ding, Huang Ningxin, Wenting Xu","doi":"10.1109/ICMLC56445.2022.9941292","DOIUrl":"https://doi.org/10.1109/ICMLC56445.2022.9941292","url":null,"abstract":"Currently VANETs still face many serious security issues. One of which is attacks from worms. To prevent the propagation of worms, different immune strategies have been proposed. One problem with these strategies is that they adopt a greedy strategy or random strategy to select immune nodes. These strategies do not consider the dynamic changes of the network topology caused by vehicle movement, which means that the strategies cannot effectively prevent a worm from spreading. In this paper, we propose a dynamic immune strategy. Considering the dynamic changes of VANETs, we use machine learning methods to predict vehicle positions at the next moment and combine the position information of vehicles at different times to evaluate the influence of a vehicle. We provide a method for computing the influence of vehicles. The vehicles with a large influence are selected as immune nodes. We compare the proposed immune strategy with several typical strategies, preemptive immunization, interactive immunization, blacklist isolation and degree immunization. The results show that the proposed method can prevent the spread of worms more effectively than existing techniques.","PeriodicalId":117829,"journal":{"name":"2022 International Conference on Machine Learning and Cybernetics (ICMLC)","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116451823","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}
Pub Date : 2022-09-09DOI: 10.1109/ICMLC56445.2022.9941304
Shogo Kotani, Masaki Nakamura, K. Sakakibara, Tatsuo Motoyoshi, Keisuke Hoshikawa
This study uses Formal Concept Analysis (FCA) to investigate factors of traffic accidents by analyzing actual traffic accident data including its date, place, injury severity, road shape, accident summary in a natural language, etc for each accident. FCA is a mathematical theory of data analysis based on formal contexts and concept lattices. We gather data related to each of the traffic accidents such as land use districts, traffic volumes, and so on, translate them into a binary context table as an input of FCA, and analyze conceptual structures as an output of FCA to investigate traffic accident factors.
{"title":"Toward Prediction of Traffic Accidents Using Formal Concept Analysis of Actual Accidents and Related Data","authors":"Shogo Kotani, Masaki Nakamura, K. Sakakibara, Tatsuo Motoyoshi, Keisuke Hoshikawa","doi":"10.1109/ICMLC56445.2022.9941304","DOIUrl":"https://doi.org/10.1109/ICMLC56445.2022.9941304","url":null,"abstract":"This study uses Formal Concept Analysis (FCA) to investigate factors of traffic accidents by analyzing actual traffic accident data including its date, place, injury severity, road shape, accident summary in a natural language, etc for each accident. FCA is a mathematical theory of data analysis based on formal contexts and concept lattices. We gather data related to each of the traffic accidents such as land use districts, traffic volumes, and so on, translate them into a binary context table as an input of FCA, and analyze conceptual structures as an output of FCA to investigate traffic accident factors.","PeriodicalId":117829,"journal":{"name":"2022 International Conference on Machine Learning and Cybernetics (ICMLC)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122066839","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}
Pub Date : 2022-09-09DOI: 10.1109/ICMLC56445.2022.9941321
Pakamas Kanchanakantikul, S. Nootyaskool
Nowadays, Algorithm trading in community and stock is interesting research, while gold is also an investment option. This research presents two steps. Three inputs sequence consists of the gold price(sell), gold spot and crude oil. Output has an order sequence indicating buy, sell, and wait for the signal. Firstly, finding the best strategy from historical data by particle swarm optimization (PSO) compared with random search (RS). That will get buying, selling, or waiting signals in the gold trading market Secondly, creating gold investment by recurrent neural network (RNN) model. The experiment result showed RNN trading model based on PSO is better than RS, which has a profit of 79.667 percent.
{"title":"Gold Investment Model on RNN and Finding Best Investment Strategy on PSO","authors":"Pakamas Kanchanakantikul, S. Nootyaskool","doi":"10.1109/ICMLC56445.2022.9941321","DOIUrl":"https://doi.org/10.1109/ICMLC56445.2022.9941321","url":null,"abstract":"Nowadays, Algorithm trading in community and stock is interesting research, while gold is also an investment option. This research presents two steps. Three inputs sequence consists of the gold price(sell), gold spot and crude oil. Output has an order sequence indicating buy, sell, and wait for the signal. Firstly, finding the best strategy from historical data by particle swarm optimization (PSO) compared with random search (RS). That will get buying, selling, or waiting signals in the gold trading market Secondly, creating gold investment by recurrent neural network (RNN) model. The experiment result showed RNN trading model based on PSO is better than RS, which has a profit of 79.667 percent.","PeriodicalId":117829,"journal":{"name":"2022 International Conference on Machine Learning and Cybernetics (ICMLC)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123776149","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}
Pub Date : 2022-09-09DOI: 10.1109/ICMLC56445.2022.9941306
Youpeng Yang, Sanhgyuk Lee, Haolan Zhang, W. Pedrycz
In this paper, we propose a concept on fuzzy soft set with negative hesitation degree. Considering the unclear information on fuzzy sets, it is represented as the overlap with the intersection of known sets over the universe of discourse. The hesitation part is clarified with detail by analyzing the overlap area belonging to the intersection of known sets or not involving in any known sets. It also resolves the limitations in intuitionistic fuzzy sets and Pythagorean fuzzy sets. With the combination of membership degree and non-membership degree, (negative)hesitation is defined in their domain. From the definition, it is more flexible for fuzzy sets characterizing when the negative hesitation degree used to describe information.
{"title":"Negative Hesitation Soft Fuzzy Sets and its Application on Decision Making Problems","authors":"Youpeng Yang, Sanhgyuk Lee, Haolan Zhang, W. Pedrycz","doi":"10.1109/ICMLC56445.2022.9941306","DOIUrl":"https://doi.org/10.1109/ICMLC56445.2022.9941306","url":null,"abstract":"In this paper, we propose a concept on fuzzy soft set with negative hesitation degree. Considering the unclear information on fuzzy sets, it is represented as the overlap with the intersection of known sets over the universe of discourse. The hesitation part is clarified with detail by analyzing the overlap area belonging to the intersection of known sets or not involving in any known sets. It also resolves the limitations in intuitionistic fuzzy sets and Pythagorean fuzzy sets. With the combination of membership degree and non-membership degree, (negative)hesitation is defined in their domain. From the definition, it is more flexible for fuzzy sets characterizing when the negative hesitation degree used to describe information.","PeriodicalId":117829,"journal":{"name":"2022 International Conference on Machine Learning and Cybernetics (ICMLC)","volume":"86 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126172074","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}
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