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检索条件"主题词=computational and artificial intelligence"

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artificial immune systems - a new emerging technology of computational intelligence - implications on development of the autonomous intelligent systems, data mining and other hybrid intelligent systems

Artificial immune systems - a new emerging technology of com...

引用

International Conference on Telecommunications (ConTEL)

作者： M.G.H. Negoita School of Information Technology Wellington Institute of Technology Wellington New Zealand

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Knowledge Representation and Learning Mechanism Based on Networks of Spiking Neurons

Knowledge Representation and Learning Mechanism Based on Net...

引用

IEEE International Conference on Systems, Man and Cybernetics

作者： QingXiang Wu David Bell Guilin Qi Jianyong Cai School of Computer Science Queen's University Belfast UK School of Physics and OptoElectronics Technology Fujian Normal University China

Knowledge representation is very important in intelligent systems -e.g. for knowledge discovery, data mining, and machine learning. The human brain, a significant intelligent system, works with a huge number of spiking neurons. Based on spiking neuron models a new generation of spiking neural networks (SNNs) has been developed for artificial intelligence systems. SNNs are computationally more powerful than conventional artificial neural networks. In this paper, the spiking neuron model is applied to represent logic rules and fuzzy rules. Based on the STDP (Spike Timing Dependent Plasticity) principle, a new SNN model is proposed for pattern recognition. An efficient learning rule derived from the STDP is applied for self-organizing the input training set efficiently. An example, Animal-Growth-Record, is used to explain the principle of the SNN model. Benchmark data sets are applied to compare the proposed approach with other approaches. As there are very efficient learning rules in the SNN model, the model can be applied not only for fusion of multi-sensory data, but also for data mining in large databases with large numbers of attributes.

关键词： Knowledge representation Learning systems Neurons Power system modeling Intelligent systems computational and artificial intelligence Data mining artificial neural networks Fuzzy logic Machine learning

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artificial Endocrine System and Applications

Artificial Endocrine System and Applications

引用

Chinese Control Conference (CCC)

作者： Cui Wei Sheng Qiang X Z Gao Department of Control Science and Engineering Harbin Institute of Technology Harbin China Institute of Intelligent Power Electronics Helsinki University of Technology Espoo Finland

Inspired by the biological immune system, the artificial endocrine system (AES) has drawn great research interest from different communities during the past decade. The AES is a novel branch of computational intelligence methods. This paper gives a comprehensive overview of the AES under a preliminary theoretical framework, which is based on the interpretative models of biological endocrine system. Some typical AES-based algorithms with their applications are discussed here. We address a few key issues in the current state-of-the-art AES research work. The possible future directions of the AES are also pointed out.

关键词： Endocrine system Feedback Power engineering and energy Programmable logic arrays computational and artificial intelligence Competitive intelligence Power electronics Immune system computational intelligence Biological system modeling

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A New Approach to Load Flow Solutions for Radial Distribution System

A New Approach to Load Flow Solutions for Radial Distributio...

引用

IEEE/PES Transmission and Distribution Conference and Exposition: Latin America

作者： T. Thakur Jaswanti Dhiman Department of Electrical Engineering Punjab Engineering College Chandigarh India

This paper presents a new approach to load flow solutions for radial distribution system, in which the choice of the switches to be opened is based on the calculation of voltage at the buses, real and reactive power flowing through lines, real power losses and voltage deviation, using distribution load flow (DLF) program. In the process of load flow calculation, two developed matrices bus injection to bus current (BIBC) and branch current to bus voltage (BCBV), and a simple matrix multiplication are used to obtain load flow solutions. The solution converges very early on; therefore execution time is very small. Particular attention is paid to the relationship between electrical parameters of the distribution system and the mathematical parameters that influence the convergence properties of the algorithm. The results reveal the speed and the effectiveness of the proposed method for solving the problems

关键词： Load flow Voltage Power engineering and energy Switches System testing Reactive power Heuristic algorithms Load management Mathematical programming computational and artificial intelligence

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A Hybrid Optimization Algorithm based on Clonal Selection Principle and Particle Swarm intelligence

A Hybrid Optimization Algorithm based on Clonal Selection Pr...

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International Conference on Intelligent Systems Design and Applications (ISDA)

作者： Qiaoling Wang Changhong Wang X.z. Gao Space Control and Inertial Technology Research center Harbin Institute of Technology Harbin China Institute of Intelligent Power Electronics Helsinki University of Technology Espoo Finland

This paper first discusses the background knowledge of the clonal selection algorithm and particle swarm method. The clonal selection algorithm is imitated by the basic principle of the adaptive immune response to virus stimulus. The particle swarm optimization is motivated by the social behaviors of swarms. Inspired by these two optimization methods, we propose a hybrid optimization algorithm in this paper. The steps of this hybrid optimization algorithm are described in details, and its performance is evaluated hybrid unidimensional function optimization and three multidimensional functions optimization problems. It is also compared with both the clonal selection algorithm and particle swarm method based on numerical simulations

关键词： Particle swarm optimization Space technology Immune system Cloning Optimization methods computational modeling Multidimensional systems Numerical simulation Power electronics computational and artificial intelligence

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Clonal Selection Algorithm with Hyper Mutation and Spatial Clone Extension

Clonal Selection Algorithm with Hyper Mutation and Spatial C...

引用

International Conference on computational intelligence and Security

作者： Zongxin Jin Guangyuan Liu Wanhui Wen Faculty of Computer & Information Science Southwest University Chongqing China

ISBN: (纸本)1424406048

In this paper, hyper mutation and spacial clone extension to antibody was introduced to the basic clonal selection algorithm mode (BCSA) in order to overcome premature convergence and stagnation at the end stage of iterative optimization. Compared to other intelligent algorithms and the BCSA after testing several typical benchmark problems, the clonal selection algorithm with hyper mutation and spatial clone extension (HSCSA) indeed managed to improve the ability of searching the global optimum and yielded superior results

关键词： Genetic mutations Cloning Iterative algorithms Immune system Testing computational and artificial intelligence Biology computing Computer networks Information science Convergence

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Software Supported Pattern Development in intelligence Analysis

Software Supported Pattern Development in Intelligence Analy...

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IEEE International Conference on computational intelligence for Homeland Security and Personal Safety (CIHSPS)

作者： Michael Wolverto Ian Harrison John Lowrance Andres Rodriguez Jerome Thomere Artificial Intelligence Center SRI International Menlo Park CA USA

intelligence professionals work with incomplete and noisy data. Their information needs are often hard to express, and almost impossible to get right the first time. This paper describes the GEM pattern language for encoding analysts' information needs in graphical patterns, and its use in the Link Analysis Workbench (LAW) system to find inexact matches to those patterns in large relational data sets. The LAW user typically interacts with the system through a cycle in which the user (1) creates an initial GEM pattern corresponding to his information need, (2) uses the LAW matcher to retrieve a collection of matching episodes in the data, (3) revises the pattern based on the shortcomings of the matches, and (4) repeats the process until the revised pattern is returning the right data. The pattern language and the system are designed to facilitate the user in quickly traversing this cycle

关键词： Pattern analysis Pattern matching Software safety Information analysis computational intelligence Terrorism Domestic safety USA Councils computational and artificial intelligence Competitive intelligence

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computational intelligence and Judgement-Based Decisions

Computational Intelligence and Judgement-Based Decisions

引用

Conference of the North American Fuzzy Information Processing Society - NAFIPS

作者： Lorna Strobel Stewart Alaleh Azad B. Eng Toronto 912-77 Finch Ave. East Toronto Ontario allie@***

People had trouble crunching numbers, so they invented computers technology that uses binary logic and strings of zeros and ones to calculate. On the other hand, people were, and still are, fairly good at adding up opinions, warnings, and probabilities in their heads, then "going with the gut". They survive by using soft information to compare the present to the past, then drawing conclusions about possible future consequences. And, they do this without the help of computers. Even though these mental extrapolations are essential to survival, they are not without risk. Many things render judgement calls inconsistent, arbitrary, or even wrong - lack of experience, moods, the time of day, and cognitive biases. Currently, computers lack the algorithms that would allow them to help reduce these risks. In this presentation, the patented Daams-Stewart algorithm is introduced. Using a new fuzzy implication operator, it captures the cognitive process of extrapolating from experience, and, at the same time, reduces the errors in judgement that creep into human reasoning. The result is computationally intelligent technology that uses soft-computing methods to reduce the risks inherent in the intuitive extrapolations that go on inside the heads of decision-makers

关键词： computational intelligence Uncertainty Intelligent agent Competitive intelligence Extrapolation Decision making computational and artificial intelligence Logic Mood Fuzzy reasoning

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A Tool for Intelligent Customer Analytics

A Tool for Intelligent Customer Analytics

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International IEEE Conference on Intelligent Systems, IS

作者： Detlef D Nauck Dymitr Ruta Martin Spott Ben Azvine BT Group Chief Technology Office Research Intelligent Systems Research Centre and Venturing Ipswich UK

Businesses collect and keep large volumes of customer data as part of their processes. Analysis of this data by business users often leads to discovery of valuable patterns and trends that otherwise would go unnoticed and that can lead to prioritization of decisions on future investments. The majority of tools currently available to business users are typically limited to computing summary statistics, simple visualization and reporting of data. More complex tools that could offer possible explanations for observations, discover knowledge, or allow making predictions are usually aimed at an academic audience or at users who are highly trained in analytics. However, it is business users with little experience in analytics who require access to tools that allow them to easily model customer behavior and build future scenarios. In this paper we present a tool we developed for business users to perform advanced analysis on customer data

关键词： Competitive intelligence Data analysis Business Learning systems computational and artificial intelligence Bayesian methods Machine learning Network servers Management training Algorithm design and analysis

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On intelligence Science and Recent Progresses

On Intelligence Science and Recent Progresses

引用

IEEE International Conference on Cognitive Informatics

作者： Zhongzhi Shi Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing China

ISBN: (纸本)9781424404759

Summary form only given. intelligence science is a cross-discipline that dedicates to joint research on basic theory and technology of intelligence by brain science, cognitive science, artificial intelligence and others. Brain science explores the essence of brain, research on the principle and model of natural intelligence in molecular, cell and behavior level. Cognitive science studies human mental activity, such as perception, learning, memory, thinking, consciousness etc. In order to implement machine intelligence, artificial intelligence attempts simulation, extension and expansion of human intelligence using artificial methodology and technology. The above three disciplines work together to explore new concept, new theory, new methodology. It will be successful and create a brilliant future in the 21 century. Brain science points out that perceptive lobes have special function separately, the occipital lobe processes the visual information, the temporal lobe processes auditory information, the parietal lobe processes the information from the somatic sensors. All of three lobes deal with information perceived from the physical world. Each lobe is covered with cortex where the bodies of neurons are located. Cortex consists of primary, intermediate and advanced areas at least. Information is processed in the primary area first, then is passed to intermediate and advanced areas. Comparing with computer system, the brain is the same as hardware and the mind looks like software. Most work in cognitive science assumes that the mind has mental representations analogous to computer data structures, and computational procedures similar to computational algorithms. Connectionists have proposed novel ideas to use neurons and their connections as inspirations for data structures, and neuron firing and spreading activation as inspirations for algorithms. Cognitive science then works with a complex 3-way analogy among the mind, the brain, and computers. Mind, brain, and comp

关键词： artificial intelligence Cognitive science Learning systems Neurons Brain modeling Humans Data structures computational and artificial intelligence Machine intelligence Temporal lobe

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