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检索条件"机构=Center for Applied Research on Soft Computing and Intelligent Systems"

共 54 条记录，以下是41-50 订阅

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Perception-based evolutionary optimization: Outline of a novel approach to optimization and problem solving

Perception-based evolutionary optimization: Outline of a nov...

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IEEE International Conference on systems, Man and Cybernetics

作者： Alireza Rowhanimanesh Mohammad-R. Akbarzadeh-T Cognitive Computing Laboratory Center of Applied Research on Soft Computing and Intelligent Systems (CARSIS) Ferdowsi University of Mashhad Mashhad Iran

Human perception and processing of information is granular and multi-resolution instead of numerical and precise. Due to this multi-resolution perception-based computing, human mind can quickly evaluate (calculate) the fitness of a large subspace of the search space. Indeed, this characteristic enables human to simplify and solve very complex problems. In contrast, evolutionary optimization (EO) as one of the most applied artificial problem solvers is based on computing with numbers since a chromosome is a single point of the search space and fitness function calculation is numerical. Hence, EO is blind towards the optimization landscape and this blindness inhibits its performance when the search space is very large and complex. Inspired by human perception based reasoning, a novel approach to optimization and problem solving is proposed here. Perception-based evolutionary optimization (PEO) is fundamentally based on computing with words. In PEO, chromosomes and fitness function calculation are perception-based (granular) instead of numerical and thus PEO works with granules (subspaces) rather than single points. Also, search is performed in a multi-resolution manner.

关键词： Benchmark testing Optimization Humans

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Fuzzy-Bayesian network approach to genre-based recommender systems

Fuzzy-Bayesian network approach to genre-based recommender s...

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IEEE International Conference on Fuzzy systems (FUZZ-IEEE)

作者： Soheila Ashkezari-T Mohammad-R. Akbarzadeh-T Department of Computer Engineering Cognitive Computing Laboratory Center of Applied Research on Soft computing and Intelligent systems Ferdowsi University of Mashhad Mashhad Iran Departments of Electrical Engineering and Computer Engineering Cognitive Computing Laboratory Center of Applied Research on Soft computing and Intelligent systems Ferdowsi University of Mashhad Iran

The World Wide Web has created a new media for mass marketing that can also be highly customized to online customers' needs and expectations. Recommender systems (RS) play an important role in this area. Here, we aim to establish a genre-based collaborative RS to automatically suggest and rank a list of appropriate items (movies) to a user based on the user profile and the past voting patterns of other users with similar tastes. The contribution of this paper is using genre based information in a hybrid fuzzy-Bayesian network collaborative RS. The interest to the different genres is computed based on a hybrid user model. The similarity of like-minded users according to the fuzzy distance and also Pearson correlation coefficient is involved in a Bayesian network.

关键词： Motion pictures Mathematical model Collaboration Recommender systems Equations Computational modeling

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A multi Adaptive Neuro Fuzzy Inference System for Short Term Load Forecasting by using previous day features

A multi Adaptive Neuro Fuzzy Inference System for Short Term...

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2010 International Conference on Electronics and Information Engineering, ICEIE 2010

作者： Souzanchi-K, Zohreh Fanaee-T, Hadi Yaghoubi, Mahdi Akbarzadeh-T, Mohammad-R. Department of Artificial Intelligence Mashhad Branch Islamic Azad University Iran Department of Information Technology Shiraz University Shiraz Iran Islamic Azad University Mashhad Branch Iran Center for Applied Research on Soft Computing and Intelligent Systems Mashhad Iran

ISBN: (纸本)9781424476800

In this paper, the use of Adaptive Neural-Fuzzy Inference System (ANFIS) to study the design of Short-Term Load Forecasting (STLF) systems for the east of Iran was explored. This paper forecasts consumed load by using multi ANFIS. Entries of the presented model are into the multi ANFIS including the date of the day, temperature maximum and minimum, climate condition and the previous days consumed load and its exit is forecasting of power load consumption of every season. Previous days contain 2,7,14 day before, and 2, 3, 4 day before. The results show that temperature and the features of 2, 7 and 14 day ago have an important role in load forecast. © 2010 IEEE.

关键词： Forecasting

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Modeling and forecasting short-term electricity load based on multi Adaptive Neural-Fuzzy Inference System by using temperature

Modeling and forecasting short-term electricity load based o...

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2010 2nd International Conference on Signal Processing systems, ICSPS 2010

作者： Zohreh, Soozanchi-K Yaghobi, Mahdi Akbarzadeh-T, Mohammad-R. Habibipour, Maryam Department of Artificial Intelligence Islamic Azad University Mashhad Branch Iran Islamic Azad University Mashhad Branch Iran Center for Applied Research Soft Computing and Intelligent Systems Mashhad Iran Sama Organization Islamic Azad University Mashhad Branch Iran

ISBN: (纸本)9781424468911

In this paper, the use of Adaptive Neural-Fuzzy Inference System (ANFIS) to study the design of Short-Term Load Forecasting (STLF) systems for the east of Iran was explored. While reviewing the probability of chaos and predictability of electricity load curve by Lyapunov exponent, this paper forecasts consumed load by using multi ANFIS. Entries of the presented model are into the multi ANFIS including the date of the day, temperature maximum and minimum, climate condition and the previous days consumed load and its exit is forecasting of power load consumption of every season. The results show that temperature has an important role in load forecast. © 2010 IEEE.

关键词： Lyapunov functions

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An intelligent system for diagnosing sleep stages using wavelet coefficients

An intelligent system for diagnosing sleep stages using wave...

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2010 6th IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 International Joint Conference on Neural Networks, IJCNN 2010

作者： Vatankhah, Maryam Akbarzadeh-T., Mohammad-R. Moghimi, Ali Islamic Azad University Mashhad Branch Iran Center for Applied Research on Intelligent Systems and Soft Computing Departments of Electrical Engineering and Computer Engineering Ferdowsi University of Mashhad Iran Dept. of Biology Faculty of Sciences Ferdowsi University of Mashhad [FUM Iran

ISBN: (纸本)9781424469178

Human sleep is divided into two segments, Rapid Eye Movement (REM) sleep and Non-REM (NREM) sleep. NREM sleep is further divided into 4 stages. Sleep staging attempts to identify these stages based on the signals collected in PSG. Significant information can be derived from the EEG signals collected during PSG. Wavelet coefficients are extracted from EEG signals. In order to reduce the amount of data set, the statistical features are calculated from wavelet coefficients. For performing decision making, six ANFIS classifiers and SVM classifier are used to differentiate between REM and Non-REM sleep stages. That is to say, pattern varies under the different sleep stages. Therefore, healthy humans with a regular night's sleep will follow these sleep stages in a particular pattern. © 2010 IEEE.

关键词： intelligent systems

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A probabilistic fuzzy approach for sensor location estimation in wireless sensor networks

A probabilistic fuzzy approach for sensor location estimatio...

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IEEE International Conference on Fuzzy systems (FUZZ-IEEE)

作者： Mahnaz Kadkhoda Mohammad-R Akbarzadeh Totounchi Mohammad. H. Yaghmaee Zohreh Davarzani Department of Computer Engineering Ferdowsi University of Mashhad Mashhad Iran Department of Electrical Engineering and Computer Engineering Center for Applied Research on Soft computing and Intelligent systems Ferdowsi University of Mashhad Iran

Nowadays, wireless sensor networks are widely used in a variety of applications such as in military, vehicle tracking, disaster management and environmental monitoring. Accurate estimation of the sensor position can be crucial in many of these applications. In this research, we propose a localization algorithm based on probabilistic fuzzy logic systems (PFLS) for range-free localization. The algorithm utilizes received signal strength (RSS) from the anchor nodes embedded with variant degrees of environmental noise. The proposed system is compared with another algorithm based on Fuzzy Logic systems (FLS) against variant amount of noise. Simulation results demonstrate that FLS can be much more accurate than PFLS method if the environment is noise-free. However, as the environmental noise increases, the PFLS reaches better performance.

关键词： Probabilistic logic Fuzzy logic Fuzzy systems Noise Wireless sensor networks Uncertainty Input variables

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A multi Adaptive Neuro Fuzzy Inference System for short term load forecasting by using previous day features

A multi Adaptive Neuro Fuzzy Inference System for short term...

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International Conference on Electronics And Information Engineering (ICEIE)

作者： Zohreh Souzanchi-K Hadi Fanaee-T Mahdi Yaghoubi Mohammad-R. Akbarzadeh-T Department of Artificial Intelligence Islamic Azad University Iran Department of Information Technology Shiraz University Shiraz Iran Islamic Azad University Iran Center for Applied Research on Soft Computing and Intelligent Systems Mashhad Iran

关键词： Load forecasting Load modeling Predictive models Forecasting Artificial neural networks Adaptation model Autoregressive processes

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Modeling and forecasting short-term electricity load based on multi adaptive neural-fuzzy inference system by using temperature

Modeling and forecasting short-term electricity load based o...

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International Conference on Signal Processing systems, ICSPS

作者： Zohreh Soozanchi-K Mahdi Yaghobi Mohammad-R. Akbarzadeh-T Maryam Habibipour Department of Artificial Intelligence Islamic Azad University Iran Department of Artificial Intelligence Mashhad Branch Iran Islamic Azad University Mashhad Branch Iran Center for Applied Research Soft Computing and Intelligent Systems Mashhad Iran Sama Organization (affiliated with Islamic Azad University) Mashhad Branch Iran

关键词： Load forecasting Load modeling Predictive models Forecasting Artificial neural networks Time series analysis Adaptation model

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An intelligent system for diagnosing sleep stages using wavelet coefficients

An intelligent system for diagnosing sleep stages using wave...

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International Joint Conference on Neural Networks (IJCNN)

作者： Maryam Vatankhah Mohammad-R. Akbarzadeh-T. Ali Moghimi Departments of Electrical Engineering and Computer Engineering Ferdowsi University of Mashhad Iran Mashhad Branch ungyo researcher club members Islamic Azad University Center for Applied Research on Intelligent Systems and Soft Computing Departments of Electrical Engineering and Computer Engineering Ferdowsi University of Mashhad Iran Department of Biology Faculty of Sciences University of Mashhad Iran

关键词： Support vector machines Time frequency analysis

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AAAI 2008 workshop reports

AAAI 2008 workshop reports

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作者： Anand, Sarabjot Singh Bunescu, Razvan Carvcdho, Vitor Chomicki, Jan Conitzer, Vincent Cox, Michael T. Dignum, Virginia Dodds, Zachary Dredze, Mark Furcy, David Gabrilovich, Evgeniy Göker, Mehmet H. Guesgen, Hans Hirsh, Haym Jannach, Dietmar Junker, Ulrich Ketter, Wolfgang Kobsa, Alfred Koenig, Sven Lau, Tessa Lewis, Lundy Matson, Eric Metzler, Ted Mihalcea, Rada Mobasher, Bamshad Pineau, Joelle Poupart, Pascal Raja, Anita Ruml, Wheeler Sadeh, Norman Shani, Guy Shapiro, Daniel Smith, Trey Taylor, Matthew E. Wagstaff, Kiri Walsh, William Zhou, Rong Department of Computer Science University of Warwick United Kingdom School of Electrical Engineering and Computer Science Ohio University United States Microsoft Live Labs United States computer science and engineering University at Buffalo United States Computer science and economics Duke University United States Intelligent Computing group of BBN Technologies Utrecht University Netherlands Department of Computer science Harvey Mudd College United States University of Pennsylvania United States University of Wisconsin United States Yahoo Research PricewaterhouseCoopers Center for Advanced Research United States Department of Computer science School of Engineering and Advanced Technology Massey University New Zealand Departent of Computer science Rutgers University United States Department of Computer Science Dortmund University of Technology. Germany ILOG Rotterdam School of Management Erasmus University Netherlands Donald Bren School of Information and Computer Sciences University of California Irvine United States Depatrment of Computer science University of Southern California United States IBM Almaden Research Center United States Department of Computer Information Technology Southern New Hampshire University United States Computer and Information Technology Program College of Technology Purdue University United States Hughes Program for Religion and Science Dialogue Oklahoma City University United States Department of Computer Science and Engineering University of North Texas United States School of Computing DePaul University United States Department of Computer Science McGill University Canada School of Computer Science University of Waterloo Canada Department of Software and Information Systems University of North Carolina Charlotte United States University of New Hampshire United States Microsoft Research Institute for the Study of Learning and Expertise Applied Reactivity Inc. United States NASA Ames Research Center Carnegie Mellon University West

AAAI was pleased to present the AAAI-08 Workshop Program, held Sunday and Monday, July 13-14, in Chicago, Illinois, USA. The program included the following 15 workshops: Advancements in POMDP Solvers;AI Education Workshop Colloquium;Coordination, Organizations, Institutions, and Norms in Agent systems, Enhanced Messaging;Human Implications of Human-Robot Interaction;intelligent Techniques for Web Personalization and Recommender systems;Metareasoning: Thinking about Thinking;Multidisciplinary Workshop on Advances in Preference Handling;Search in Artificial Intelligence and Robotics;Spatial and Temporal Reasoning;Trading Agent Design and Analysis;Transfer Learning for Complex Tasks;What Went Wrong and Why: Lessons from AI research and Applications;and Wikipedia and Artificial Intelligence: An Evolving Synergy. Copyright © 2009, Association for the Advancement of Artificial Intelligence. All rights reserved.

关键词： Human robot interaction

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