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Piecewise Linear Model Tree: A modified combination of two learning algorithms for neuro-fuzzy models

Piecewise Linear Model Tree: A modified combination of two l...

引用

IEEE International Conference on computer-Aided Design

作者： Atiye Sarabi Jamab Babak N. Araabi Electrical Engineering Department Malek Ashtar University of Technology Tehran Iran Control & Intelligent Processing Center of Excellence Electrical and Computer Engineering Department University of Tehran Tehran Iran

Locally Linear Model Tree (LOLIMOT) and Piecewise Linear Network (PLN) learning algorithms are two approaches in local linear modeling use different algorithm in each part of training phase. PLN learning is more depended on training data than LOIMOT and needs rich training data set. In PLN learning no division test is needed and it causes this algorithm to be much faster than LOLIMOT, but it may create adjacent neurons that would lead to singularity in regression matrix. In LOLIMOT, because of regular splitting of input space, this problem does not occur and always it leads to acceptable output error, but needs large number of neuron. Therefore, PILIMOT learning algorithm is introduced as modified combination of these two main Locally Linear approaches. This new method takes suitable error and neuron number from both of algorithms and leads to efficient network which is applicable to identify all functions. Simulation results show the advantage and behavior of new method.

关键词： Piecewise linear techniques Function approximation Neurons Partitioning algorithms Neural networks Approximation algorithms Piecewise linear approximation Radial basis function networks Training data Artificial neural networks

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A New Clustering Method for Improving Plasticity and Stability in Handwritten Character Recognition Systems

A New Clustering Method for Improving Plasticity and Stabili...

引用

International Conference on Pattern Recognition

作者： J. Sadri C.Y. Suen T.D. Bui CENPARMI Center for Pattern Recognition and Machine Intelligence Computer Science and Software Engineering Department Concordia University Montreal QUE Canada

This paper presents a new online clustering algorithm in order to improve plasticity and stability in handwritten character recognition systems. Our clustering algorithm is able to automatically determine the optimal number of clusters in the input data. An incremental learning technique similar to adaptive resonance theory (ART) is used to determine the best cluster for new data. Our technique also allows the previously learned clusters to be merged whenever the newly arrived data points push their centers close together. We also developed new features and similarity measures in order to describe and compare the shapes of handwritten digits to be used in our clustering algorithm. Results of our algorithm on clustering the shapes of the handwritten numerals from the CENPARMI isolated digit database are shown. Our method can incrementally learn new handwriting styles of digits, without forgetting the previous ones, therefore it can improve plasticity and stability

关键词： Clustering methods Stability Character recognition Shape measurement Clustering algorithms Prototypes Machine learning Pattern recognition Subspace constraints Neural networks

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UML-based service robot software development: A case study

UML-based service robot software development: A case study

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28th International Conference on software engineering 2006, ICSE '06

作者： Kim, Minseong Kim, Suntae Park, Sooyong Choi, Mun-Taek Kim, Munsang Gomaa, Hassan Department of Computer Science Sogang University Seoul Korea Republic of Center for Intelligent Robotics Frontier 21 Program Korea Institute of Science and Technology Seoul Korea Republic of Dept. of Information and Software Engineering George Mason University Fairfax VA 22030 United States

ISBN: (纸本)1595933751

The research field of Intelligent Service Robots, which has become more and more popular over the last years, covers a wide range of applications from climbing machines for cleaning large storefronts to robotic assistance for disabled or elderly people. When developing service robot software, it is a challenging problem to design the robot architecture by carefully considering user needs and requirements, implement robot application components based on the architecture, and integrate these components in a systematic and comprehensive way for maintainability and reusability. Furthermore, it becomes more difficult to communicate among development teams and with others when many engineers from different teams participate in developing the service robot. To solve these problems, we applied the COMET design method, which uses the industry-standard UML notation, to developing the software of an intelligent service robot for the elderly, called T-Rot, under development at center for Intelligent Robotics (CIR). In this paper, we discuss our experiences with the project in which we successfully addressed these problems and developed the autonomous navigation system of the robot with the COMET/UML method. Copyright 2006 ACM.

关键词： Intelligent robots

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Optimal evolutionary computational parameters for habitat structures optimization

Optimal evolutionary computational parameters for habitat st...

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Earth and Space 2006 - 10th Biennial International Conference on engineering, Construction, and Operations in Challenging Environments

作者： Hull, Patrick V. Sansoucie, Michael Dozier, Gerry Tinker, Mike NASA Marshall Space Flight Center Spacecraft and Vehicle Systems Dept./EV11 Huntsville AL 35812 United States Applied Computational Intelligence Lab. Department of Computer Science Amd Software Engineering Auburn University Auburn AL 36849-5347

ISBN: (纸本)0784408300

Long-duration surface missions to the Moon and Mars will require bases to accommodate habitats for the astronauts, as well as indoor laboratory facilities, in-situ resource plants, power plants, and scientific/surface mobility equipment. Transporting the materials and equipment required to build the necessary habitats would be costly and difficult. However, the use of planetary resources to produce construction materials, or even as naturally found (such as lunar regolith utilized as an outer layer for radiation shielding, or regolith in bags as wall structure), could drastically reduce the upmass for habitats. The materials chosen for the habitat walls play a direct role in protection against each of the mentioned hazards. Choosing the best materials, their configuration, and the amount required is extremely difficult due to the immense size of the design region. For example a 3-layer habitat wall created from 20 possible materials all with varying thicknesses would have #number of layers(possible material types)∧(possible thicknesses) = 320∧inf possible solutions. Clearly, an optimization method is warranted for habitat wall design. Standard optimization techniques are not suitable for problems with such large search spaces. To overcome the large search regions, a habitat wall design tool using genetic algorithms has been developed. GAs use a "survival of the fittest" philosophy, where the most fit individuals are more likely to survive and reproduce, therefore transmitting their genes to the next generation. This paper focuses on finding optimal GA parameters for the habitat optimization tool. This tool is a multiobjective formulation of structural analysis, heat loss, radiation, and meteoroid protection. Some of the constraint calculations (i.e. safety factor, deflection, and heat loss) require long computation times. Even though each material has a designated thickness range, the number of different values within that range is near infinite;therefore, the searc

关键词： Lunar missions

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Design and simulation of an adaptive load shedding algorithm using a real network

Design and simulation of an adaptive load shedding algorithm...

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IEEE Power India Conference

作者： H. Seyedi M. Sanaye-Pasand M.R. Dadashzadeh School of Electrical and Computer Engineering University of Tehran Iran Control and Intelligent Processing Center of Excellence University of Tehran Iran Department of Electrical Engineering University of Western Ontario Canada

ISBN: (纸本)0780395255

In this paper a new adaptive under frequency load shedding algorithm is designed. The purpose of this method is to enhance the adaptability of under frequency relays and increase the security of power system during large disturbances. A suitable method to design the proposed adaptive under frequency load shedding scheme is described in detail. After completing the design, it is tested on a real power system by modeling the network in a power system studies software. Simulation results indicate that the proposed method has an improved performance for large disturbances while its response is similar to the conventional scheme for small disturbances

关键词： Algorithm design and analysis Power system simulation Power system relaying Power system security Power system modeling Frequency Design methodology software testing System testing software systems

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Channel Assignment using Chaotic Simulated Annealing Enhanced Hopfield Neural Network

Channel Assignment using Chaotic Simulated Annealing Enhance...

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International Joint Conference on Neural Networks (IJCNN)

作者： A.M. Farahmand M.J. Yazdanpanah Department of Computing Science University of Alberta Canada Electrical and Computer Engineering Department Control and Intelligent Processing Center of Excellence University of Tehran Tehran Iran

Channel assignment problem in cellular communication is a difficult combinatorial optimization problem. There is no exact polynomial-time solution for it and searching the whole solution space is infeasible for large problems. By defining the problem's cost function as the energy function of a chaotic Hopfield neural network, we devise a framework for finding competitive suboptimal or even optimal solutions for combinatorial optimization problem in general, and channel assignment problem in particular. In our architecture, we inject chaotic noise in order to help the network escape from local minima of the energy function while we enforce problem constraints by external inputs of neurons. Experimental results show the superiority of our method to other methods.

关键词： Chaos Simulated annealing Hopfield neural networks Chaotic communication Neurons Interference Control engineering computing Process control Intelligent control Polynomials

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A Genetic Binary Particle Swarm Optimization Model

A Genetic Binary Particle Swarm Optimization Model

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Congress on Evolutionary Computation

作者： J. Sadri C.Y. Suen CENPARMI (Center for Pattern Recognition and Machine Intelligence) Computer Science and Software Enginneering Concordia University Montreal West QUE Canada Computer Science and Software Engineering Department Concordia University Montreal QUE Canada

In this paper, a genetic binary particle swarm optimization (GBPSO) model is proposed, and its performance is compared with the regular binary particle swarm optimizer (PSO), introduced by Kennedy and Eberhart. In the original model, the size of the swarm was fixed. In our model, we introduce birth and death operations in order to make the population very dynamic. Since birth and mortality rates change naturally with time, our model allows oscillations in the size of the population. Compared to the original PSO model, and genetic algorithms, our strategy proposes a more natural simulation of the social behavior of intelligent animals. The experimental results show that compared to original PSO, our GBPSO model can reach broader domains in the search space and converge faster in very high dimensional and complex environments.

关键词： Particle swarm optimization Multidimensional systems computer science software engineering Java Genetic algorithms Animals Adaptive algorithm Birds Educational institutions

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Issues in formulating utility functions for sensor management

Issues in formulating utility functions for sensor managemen...

引用

Signal Processing, Sensor Fusion, and Target Recognition XV

作者： Hintz, Kenneth J. Department of Electrical and Computer Engineering Center of Excellence in C4I George Mason Univ. Dept. of Elect. and Comp. Engr. M/s 1G5 4400 Univ. Dr. Fairfax VA 22030

ISBN: (纸本)0819462918

A significant difficulty associated with the real-world problem of forward air defense (FAD) is the development of a utility function which can be effectively used in allocating heterogeneous sensing resources. Several properties and desirable aspects of utility functions are discussed from the point of view of FAD. The benefits of information as a utility function are reviewed and shown to be applicable in this context.

关键词： Sensor data fusion

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A Toolbox for Brain Emotional Learning Based Intelligent Controller

A Toolbox for Brain Emotional Learning Based Intelligent Con...

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IEEE International Conference on engineering of Intelligent Systems, ICEIS

作者： A.R. Mehrabian C. Lucas Control and Intelligent Processing Center of Excellence Department of Mechanical Engineering University of Tehran Tehran Iran School of Cognitive Science Institute of Studies in Theoretical Physics and Mathematics Tehran Iran Control and Intelligent Processing Center of Excellence Department of Electrical and Computer Engineering University of Tehran Tehran Iran

Brain emotional learning based intelligent controller, BELBIC, has been used for model free adaptive control of several complex industrial plants. It has proven to be very effective controller with light computational load. The aim of this research is to present a general purpose toolbox implementing BELBIC as well as examples of its performance. The user can choose to utilize default configurations or to customize specific configuration to the given plant

关键词： Nonlinear control systems Intelligent control Intelligent structures Control system synthesis Control systems Brain modeling Process control Power system control Power system dynamics Mechanical engineering

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Multiscale Face Detection: A New Approach to Robust Face Detection

Multiscale Face Detection: A New Approach to Robust Face Det...

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IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)

作者： M. Aghagolzadeh H. Soltanian-Zadeh B.N. Araabi Department of Electrical and Computer Engineering University of Tehran Tehran Iran Radiologyimageanalaysis laboratory Henry Ford Health System Detroit MI USA Control and Intelligent Processing Center of Excellence Electrical and Computer Engineering Department University of Tehran Tehran Iran

This paper presents a novel method for detecting multiple frontal faces in still images using multi-scale processing. The main characteristic of this algorithm is its stability in detecting faces with seldom false detections and a high correct detection rate. The novelty of this work comes from the utilization of multiscale detection and using two classifiers to reduce false detections. The algorithm generally has two stages: in the first stage, a face is detected in a unique scale and in the second stage, only the faces that are located in the neighbor scales are accepted as real faces. Consequently, a still image is first resized and scanned block wise, and then each enhanced block is tested for being face. One dimensional Harr wavelet is used for feature extraction, which gives appropriate discriminating features between the face and nonface classes. Detection results at each scale are accumulated in an internal database, so the ultimate detection is prepared based on the mutual detection information between consequent scales. To parameterize both the Bayesian and the simple proposed classifier, 2,643 faces were congregated from famous face databases and more than 10,000 non-face samples were selected from nature images. Experimental results using images gathered from known databases like MIT-CMU show great ability of the proposed algorithm in detecting faces.

关键词： Face detection Robustness Image databases Bayesian methods Humans Application software Stability Feature extraction Spatial databases computer vision

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