2016 IEEE 9th International Workshop on Computational Intelligence and Applications (IWCIA)最新文献_第2页

On mining quantitative association rules from multi-relational data with FCA 基于FCA的多关系数据定量关联规则挖掘

2016 IEEE 9th International Workshop on Computational Intelligence and Applications (IWCIA) Pub Date : 2016-11-01 DOI: 10.1109/IWCIA.2016.7805753

M. Nagao, H. Seki

引用次数: 4

Recognition of persisting emotional valence from EEG using convolutional neural networks 卷积神经网络在脑电图持续情绪效价识别中的应用

2016 IEEE 9th International Workshop on Computational Intelligence and Applications (IWCIA) Pub Date : 2016-11-01 DOI: 10.1109/IWCIA.2016.7805744

Miku Yanagimoto, C. Sugimoto

{"title":"Recognition of persisting emotional valence from EEG using convolutional neural networks","authors":"Miku Yanagimoto, C. Sugimoto","doi":"10.1109/IWCIA.2016.7805744","DOIUrl":"https://doi.org/10.1109/IWCIA.2016.7805744","url":null,"abstract":"Recently there has been considerable interest in EEG-based emotion recognition (EEG-ER), which is one of the utilization of BCI. However, it is not easy to realize the EEG-ER system which can recognize emotions with high accuracy because of the tendency for important information in EEG signals to be concealed by noises. Deep learning is the golden tool to grasp the features concealed in EEG data and enable highly accurate EEG-ER because deep neural networks (DNNs) may have higher recognition capability than humans'. The publicly available dataset named DEAP, which is for emotion analysis using EEG, was used in the experiment. The CNN and a conventional model used for comparison are evaluated by the tests according to 11-fold cross validation scheme. EEG raw data obtained from 16 electrodes without general preprocesses were used as input data. The models classify and recognize EEG signals according to the emotional states \"positive\" or \"negative\" which were caused by watching music videos. The results show that the more training data are, the much higher the accuracies of CNNs are (by over 20%). It also suggests that the increased training data need not to belong to the same person's EEG data as the test data so as to get the CNN recognizing emotions accurately. The results indicate that there are not only the considerable amount of the interpersonal difference but also commonality of EEG properties.","PeriodicalId":262942,"journal":{"name":"2016 IEEE 9th International Workshop on Computational Intelligence and Applications (IWCIA)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122316448","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}

引用次数: 27

An ensemble model of self-organizing maps for imputation of missing values 缺失值估计的自组织映射集成模型

2016 IEEE 9th International Workshop on Computational Intelligence and Applications (IWCIA) Pub Date : 2016-11-01 DOI: 10.1109/IWCIA.2016.7805741

F. Saitoh

引用次数: 7

Efficiency improvement of imitation operator in multi-agent control model based on Cartesian Genetic Programming 基于笛卡尔遗传规划的多智能体控制模型中模仿算子的效率改进

2016 IEEE 9th International Workshop on Computational Intelligence and Applications (IWCIA) Pub Date : 2016-11-01 DOI: 10.1109/IWCIA.2016.7805751

Akira Hara, Hiroki Konishi, J. Kushida, T. Takahama

{"title":"Efficiency improvement of imitation operator in multi-agent control model based on Cartesian Genetic Programming","authors":"Akira Hara, Hiroki Konishi, J. Kushida, T. Takahama","doi":"10.1109/IWCIA.2016.7805751","DOIUrl":"https://doi.org/10.1109/IWCIA.2016.7805751","url":null,"abstract":"In this paper, we focus on evolutionary optimization of multi-agent behavior. In our previous work, we have proposed a multi-agent control model based on Cartesian Genetic Programming (CGP). In CGP, each individual is represented by a graph-structural program. The CGP has a characteristics that each individual has multiple output nodes. Therefore, by assigning the outputs to respective agents, we can control multiple agents by an individual. The method enables multiple agents to not only take different actions according to their own roles but also share sub-programs if the same behavior is needed for solving problems. In addition, a new genetic operator for multi-agent control, imitation operator, has been proposed to facilitate the grouping of agents. An agent selects another agent at random for imitating the behavior. However, if the number of agents increases, the appropriate agent cannot always be selected for imitation. Therefore, in this paper, we propose a modified imitation operator for selecting useful agent. We applied our method to a food foraging problem. The experimental results showed that the performance of our method is superior to those of the conventional models.","PeriodicalId":262942,"journal":{"name":"2016 IEEE 9th International Workshop on Computational Intelligence and Applications (IWCIA)","volume":"72 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126363021","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}

引用次数: 0

Cartesian ant programming with transition rule considering internode distance 考虑节点间距离的过渡规则笛卡尔蚁群规划

2016 IEEE 9th International Workshop on Computational Intelligence and Applications (IWCIA) Pub Date : 2016-11-01 DOI: 10.1109/IWCIA.2016.7805756

J. Kushida, Akira Hara, T. Takahama, Shogo Nagura

{"title":"Cartesian ant programming with transition rule considering internode distance","authors":"J. Kushida, Akira Hara, T. Takahama, Shogo Nagura","doi":"10.1109/IWCIA.2016.7805756","DOIUrl":"https://doi.org/10.1109/IWCIA.2016.7805756","url":null,"abstract":"In recent years, Cartesian Ant Programming (CAP) has been proposed as a swarm-based automatic programming method, which combines graph representations in Cartesian Genetic Programming with search mechanism of Ant Colony Optimization. In CAP, once an ant jumps a number of nodes, the skipped nodes are not utilized and wasted in search. To make the use frequency of nodes uniform, we propose CAP with transition rule considering internode distance. We focus on the distance at the beginning of search to utilize a large number of nodes for exploration of search. As the search proceeds, the search comes to depend on the pheromone information for exploitation of search. In addition, to prevent the excessive use of the unnecessary nodes, we modify the method of dynamic symbol assignments to nodes so that not only functional symbols but also terminal symbols can be assigned to the respective nodes. We examined the effectiveness of our proposed method by applying it to symbolic regression problems. From the experimental results, we confirmed the improvement of performance and the relief of bias in use frequency of nodes by our proposed method.","PeriodicalId":262942,"journal":{"name":"2016 IEEE 9th International Workshop on Computational Intelligence and Applications (IWCIA)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131966710","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}

引用次数: 2

Agent-based simulation of trust games for communication and information 基于agent的通信与信息信任博弈仿真

2016 IEEE 9th International Workshop on Computational Intelligence and Applications (IWCIA) Pub Date : 2016-11-01 DOI: 10.1109/IWCIA.2016.7805757

Tomoharu Hasegawa, Tomohiro Hayashida, I. Nishizaki, Shinya Sekizaki

引用次数: 0

Particle swarm optimization with dynamic search strategies based on landscape modality estimation 基于景观模态估计的动态搜索策略粒子群优化

2016 IEEE 9th International Workshop on Computational Intelligence and Applications (IWCIA) Pub Date : 2016-11-01 DOI: 10.1109/IWCIA.2016.7805758

Toshiki Nishio, J. Kushida, Akira Hara, T. Takahama

引用次数: 0

A stock price forecasting application using neural networks with multi-optimizer 基于多优化器的神经网络股票价格预测应用

2016 IEEE 9th International Workshop on Computational Intelligence and Applications (IWCIA) Pub Date : 2016-11-01 DOI: 10.1109/IWCIA.2016.7805750

C. Worasucheep

引用次数: 3

Recommendation incorporating transition of temporally intensive unity 建议纳入过渡的时间密集统一

2016 IEEE 9th International Workshop on Computational Intelligence and Applications (IWCIA) Pub Date : 2016-11-01 DOI: 10.1109/IWCIA.2016.7805743

Kenta Inuzuka, Tomonori Hayashi, T. Takagi

引用次数: 1

Recommending paragraphs of wikipedia pages as a travel guide 推荐维基百科页面的段落作为旅游指南

2016 IEEE 9th International Workshop on Computational Intelligence and Applications (IWCIA) Pub Date : 2016-11-01 DOI: 10.1109/IWCIA.2016.7805749

M. Tokuhisa, Yuuki Ishihara, Shuhei Kimura, Kenta Oku

引用次数: 2