Search Results 1-20 of 186

  • Human Detection using Hardware Oriented GMM-MRCoHOG  [in Japanese]

    Nagamine Yuya , Yoshihiro Kazuki , Shibata Masatoshi , Yamada Hideo , Enokida Shuichi , Tamukoh Hakaru

    … So, We proposed two methods for solving each problem. … Second, use fuzzy inference for saving memory resources. … The experimental results show that these methods maintain high accuracy with reduce in calculation cost and memory resources.</p> …

    Proceedings of the Fuzzy System Symposium 35(0), 715-719, 2019


  • Design Evaluation of Learning Type Fuzzy Inference Using Trapezoidal Membership Function  [in Japanese]

    IRIE Honoka , HAYASHI Isao

    … <p>Trapezoidal fuzzy inference is a general form of triangular fuzzy reasoning, that has proven to be effective at solving various types of inference problems. … When used as a clustering method, fuzzy inference allows for adjusting cluster boundaries with each new datapoint. …

    Journal of Japan Society for Fuzzy Theory and Intelligent Informatics 31(6), 908-917, 2019


  • Noise Reduction with Fuzzy Inference Based on Generalized Mean and Singleton Input–Output Rules: Toward Fuzzy Rule Learning in a Unified Inference Platform

    Uehara Kiyohiko , Hirota Kaoru

    … <p>A method is proposed for reducing noise in learning data based on fuzzy inference methods called α-GEMII (α-level-set and generalized-mean-based inference with the proof of two-sided symmetry of consequences) and α-GEMINAS (α-level-set and generalized-mean-based inference with fuzzy rule interpolation at an infinite number of activating points). …

    Journal of Advanced Computational Intelligence and Intelligent Informatics 23(6), 1027-1043, 2019


  • A Fuzzy Inference-Based Spiking Neural Network for Behavior Estimation in Elderly Health Care System

    Shao Shuai , Kubota Naoyuki

    … We found that traditional methods have difficulty solving the problem of excessive indoor environmental differences in different households. … Therefore, we provide a fuzzy spike neural network. … By modifying the sensitivity of input using a fuzzy inference system, we can solve the problem without additional training. …

    Journal of Advanced Computational Intelligence and Intelligent Informatics 23(3), 528-535, 2019


  • Learning Methods for Fuzzy Inference System Using Vector Quantization  [in Japanese]

    MIYAJIMA Hirofumi , KUBUKI Hiromu , SHIGEI Noritaka , MIYAJIMA Hiromi

    … <p>Many studies on fuzzy modeling (learning of fuzzy inference systems) with vector quantization (VQ) and steepest descend method (SDM) have been made. … It is known that they are superior in the number of rules (parameters) compared with other learning methods. …

    Journal of Japan Society for Fuzzy Theory and Intelligent Informatics 31(2), 690-699, 2019


  • Feature Selection Method for Real-time Speech Emotion Recognition

    Elbarougy Reda , Akagi Masato

    … These traditional methods does not reflect all types of relations between acoustic features and emotional state. … However, the relationship between any two variables can be linear, nonlinear or fuzzy. … Therefore, a feature selection method based on fuzzy inference system (FIS) was proposed. … The experimental results reveal that the proposed features selection method outperforms the traditional methods. …

    2017 20th Conference of the Oriental Chapter of the International Coordinating Committee on Speech Databases and Speech I/O Systems and Assessment (O-COCOSDA), 86-91, 2017-11-01


  • Complimentary Address

    Rudas Imre

    … One of the greatest merit of the journal is that it is able be serve as a common platform for the most relevant researchers and societies in order to expand the boundaries of many related fields including Fuzzy Logic, NeuralNetworks, Genetic and Evolutionary Computation, Biologically-Inspired Computation Systems and so on.<br>In these days the most up-coming challenges are connected to the topics of JACIII including the current special issue as well. …

    Journal of Advanced Computational Intelligence and Intelligent Informatics 21(1), 6-6, 2017


  • Fuzzy Inference Based on α-Cuts and Generalized Mean: Relations Between the Methods in its Family and their Unified Platform

    Uehara Kiyohiko , Hirota Kaoru

    … <p>This paper clarifies the relations in properties and structures between fuzzy inference methods based on α-cuts and the generalized mean. … The group of the inference methods is named the α-GEM (α-cut and generalized-mean-based inference) family. …

    Journal of Advanced Computational Intelligence and Intelligent Informatics 21(4), 597-615, 2017


  • Fuzzy Inference: Its Past and Prospects

    Uehara Kiyohiko , Hirota Kaoru

    … <p>Fuzzy inference in the past and its future prospects are described to further promote research in the field: First, the basic methods of fuzzy inference are introduced. … Then, the progress of fuzzy inference is reviewed, showing its remarkable achievements, especially in industries. …

    Journal of Advanced Computational Intelligence and Intelligent Informatics 21(1), 13-19, 2017


  • Velocity Control System Based on Fuzzy Inference by Detecting Vibration with Acceleration Sensor  [in Japanese]

    AIBA Futoshi , OKAWA Kazuya

    … Conventional vibration control methods obtain effect after receiving vibration, so that it cannot deal with impulsive vibration. … At first, fuzzy inference calculates an appropriate velocity from detected vibration and current velocity. …

    The Proceedings of JSME annual Conference on Robotics and Mechatronics (Robomec) 2017(0), 2A2-C07, 2017


  • Using a Single Dendritic Neuron to Forecast Tourist Arrivals to Japan

    CHEN Wei , SUN Jian , GAO Shangce , CHENG Jiu-Jun , WANG Jiahai , TODO Yuki

    … Traditional forecasting methods usually suffer from the prediction accuracy problem due to the high volatility, irregular movements and non-stationarity of the tourist time series. … Experimental results of the forecasting of the monthly foreign tourist arrivals to Japan indicate that the proposed SDNM is more efficient and accurate than other neural networks including the multi-layered perceptron, the neuro-fuzzy inference system, the Elman network, and the single multiplicative neuron model.</p> …

    IEICE Transactions on Information and Systems E100.D(1), 190-202, 2017


  • Fuzzy Inference : Basic Methods and Their Extensions(Part 2)  [in Japanese]

    上原 清彦 , 廣田 薫

    知能と情報 28(5), 141-148, 2016-10

  • Fuzzy Inference : Basic Methods and Their Extensions(Part 1)  [in Japanese]

    上原 清彦 , 廣田 薫

    知能と情報 28(4), 107-112, 2016-08

  • Studies on inference system of deep body temperature by using machine learning methods  [in Japanese]

    宮島 洋文 , 樽見 航 , 土居 裕和 , 小林 透 , 篠原 一之

    電子情報通信学会技術研究報告 = IEICE technical report : 信学技報 116(138), 57-62, 2016-07-15

  • Pruned Fast Learning Fuzzy Approach for Data-Driven Traffic Flow Prediction

    Li Chengdong , Lv Yisheng , Yi Jianqiang , Zhang Guiqing

    … With the rapid growth of traffic flow data, fast and accurate traffic flow prediction methods are now required. … In this paper, we propose a novel fast learning data-driven fuzzy approach for the traffic flow prediction problem. … In the proposed approach, to achieve fast learning, an extreme learning machine is utilized to optimize the consequent parameters of the fuzzy rules. …

    Journal of Advanced Computational Intelligence and Intelligent Informatics 20(7), 1181-1191, 2016


  • Fuzzy Inference : Basic Methods and Their Extensions (Part 1)  [in Japanese]

    UEHARA Kiyohiko , HIROTA Kaoru

    Journal of Japan Society for Fuzzy Theory and Intelligent Informatics 28(4), 107-112, 2016


  • Autonomous Movement of Tableware Clean-up Mobile Robot Based on Ease of Grasping Unknown Object  [in Japanese]

    FURUKAWA Cyril , TAMURA Yasuto , MASUTA Hiroyuki , LIM Hun-Ok

    … Many conventional grasping methods have required the accurate physical parameters of an unknown object. … The grasping sense is described by inertia tensor and fuzzy inference. …

    The Proceedings of JSME annual Conference on Robotics and Mechatronics (Robomec) 2016(0), 1A1-08a2, 2016


  • Learning System for Emotion Estimation and Emotional Expression Motion Generation based on RNN with Russell's Circumplex Model  [in Japanese]

    TSUJIMOTO Takuya , TAKAHASHI Yasutake , TAKEUCHI Shouhei , MAEDA Yoichiro

    … In our previous research, the authors have proposed the "Fuzzy Emotion Inference System(FEIS)". … The FEIS particularly focuses only on the process of "human emotion inference" by analyzing the human body motion values based on Laban's theory. … It measures the basic psychological value by fuzzy reasoning and infers the emotion based on Russell's circumplex model. …

    Journal of Japan Society for Fuzzy Theory and Intelligent Informatics 28(4), 716-722, 2016

    IR  J-STAGE 

  • Fuzzy Probability and its Application for Probability Qualified Natural Language Propositions  [in Japanese]

    Okamoto Wataru

    … In this paper, we have reviewed Zadeh's paper for fuzzy probability. … We refer to evaluation methods for probability qualified natural language propositions. …

    Proceedings of the Fuzzy System Symposium 31(0), 262-265, 2015


  • Accurate phoneme segmentation method using combination of HMM and Fuzzy Inference system

    DONG Liang , ELBAROUGY Reda , AKAGI Masato

    … Compared with this, automatic segmentation methods are much stable and faster. … Recently, some researches attempt to improve the accuracy of automatic segmentation by using some statistical correction procedures or learning methods on HMM-based forced-alignment. … This paper presents an effective approach based on an adaptive neuro fuzzy inference system (ANFIS) for refining the output of the traditional HMM. …

    IEICE technical report. Welfare Information technology 114(92), 63-68, 2014-06-19

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