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ITHEA Classification Structure > F. Theory of Computation  > F.1 COMPUTATION BY ABSTRACT DEVICES  > F.1.1 Models of Computation 
ITHEA Classification Structure > G. Mathematics of Computing  > G.1 NUMERICAL ANALYSIS  > G.1.2 Approximation 
ITHEA Classification Structure > I. Computing Methodologies  > I.2 ARTIFICIAL INTELLIGENCE  > I.2.6 Learning
POLYNOMIAL APPROXIMATION USING PARTICLE SWARM OPTIMIZATION OF LINEAR ...
By: Mingo et al. (5055 reads)
Rating: (1.00/10)

Abstract: This paper presents some ideas about a new neural network architecture that can be compared to a Taylor analysis when dealing with patterns. Such architecture is based on lineal activation functions with an axo-axonic architecture. A biological axo-axonic connection between two neurons is defined as the weight in a connection in given by the output of another third neuron. This idea can be implemented in the so called Enhanced Neural Networks in which two Multilayer Perceptrons are used; the first one will output the weights that the second MLP uses to computed the desired output. This kind of neural network has universal approximation properties even with lineal activation functions. There exists a clear difference between cooperative and competitive strategies. The former ones are based on the swarm colonies, in which all individuals share its knowledge about the goal in order to pass such information to other individuals to get optimum solution. The latter ones are based on genetic models, that is, individuals can die and new individuals are created combining information of alive one; or are based on molecular/celular behaviour passing information from one structure to another. A swarm-based model is applied to obtain the Neural Network, training the net with a Particle Swarm algorithm.

Keywords: Neural Networks, Swarm Computing, Particle Swarm Optimization.

ACM Classification Keywords: F.1.1 Theory of Computation - Models of Computation, I.2.6 Artificial Intelligence - Learning, G.1.2 Numerical Analysis - Approximation.

Link:

POLYNOMIAL APPROXIMATION USING PARTICLE SWARM OPTIMIZATION OF LINEAR ENHANCED NEURAL NETWORKS WITH NO HIDDEN LAYERS

Luis F. de Mingo, Miguel A. Muriel, Nuria Gómez Blas, Daniel Triviño G.

http://www.foibg.com/ijima/vol01/ijima01-3-p01.pdf

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F.1.1 Models of Computation
article: ALGORITHMIZATION PROCESS FOR FRACTAL ANALYSIS IN THE CHAOTIC DYNAMICS OF ... · INTELLIGENT TRADING SYSTEMS · AN ARCHITECTURE FOR REPRESENTING BIOLOGICAL PROCESSES BASED ON NETWORKS... · Polynomial Regression using a Perceptron with Axo-axonic Connections · ACCOUNTING IN THEORETICAL GENETICS · A NEW METHOD FOR THE BINARY ENCODING AND HARDWARE IMPLEMENTATION OF METABOLIC P · GENETIC BASED SPOT DETECTION METHOD IN TWO-DIMENSIONAL ELECTROPHORESIS IMAGES · Self-Organizing Architectural design based on Morphogenetic Programming · PRION CRYSTALIZATION MODEL AND ITS APPLICATION TO RECOGNITION PATTERN · POLYNOMIAL APPROXIMATION USING PARTICLE SWARM OPTIMIZATION OF LINEAR ... · MULTIPLE-MODEL DESCRIPTION AND STRUCTURE DYNAMICS ANALYSIS OF ACTIVE MOVING... · COMPUTATIONAL MODEL FOR SERENDIPITY · STRING MEASURE APPLIED TO STRING SELF-ORGANIZING MAPS AND NETWORKS OF ... · CLASSIFICATION OF DATA TO EXTRACT KNOWLEDGE FROM NEURAL NETWORKS · SIMULTANEOUS CONTROL OF CHAOTIC SYSTEMS USING RBF NETWORKS · TIMED TRANSITION AUTOMATA AS NUMERICAL PLANNING DOMAIN · STATIC ANALYSIS OF USEFULNESS STATES IN TRANSITION P SYSTEMS · GENERALIZING OF NEURAL NETS: FUNCTIONAL NETS OF SPECIAL TYPE · AUTOMATA–BASED METHOD FOR SOLVING SYSTEMS OF LINEAR CONSTRAINTS IN {0,1} · FILTERED NETWORKS OF EVOLUTIONARY PROCESSORS* · NEURAL CONTROL OF CHAOS AND APLICATIONS · SOLVING A DIRECT MARKETING PROBLEM BY THREE TYPES OF ARTMAP NEURAL NETWORKS ·
G.1.2 Approximation
article: Integrated Approach to the Study of Fractal Time Series · ALGORITHMIZATION PROCESS FOR FRACTAL ANALYSIS IN THE CHAOTIC DYNAMICS OF ... · ANALYSIS OF THE PROPERTIES OF ORDINARY LEVY MOTION BASED ON THE ESTIMATION ... · POLYNOMIAL APPROXIMATION USING PARTICLE SWARM OPTIMIZATION OF LINEAR ... · MODELING TELECOMMUNICATIONS TRAFFIC USING THE STOCHASTIC MULTIFRACTAL CASCADE... · METHODS OF RECONSTRUCTION OF SURFACE PROFILES MEASURED BY STYLUS METHOD · COMPARATIVE ANALYSIS FOR ESTIMATING OF THE HURST EXPONET FOR STATIONARY AND ... · ЛИНЕЙНОЕ ОЦЕНИВАНИЕ ПАРАМЕТРОВ МОДЕЛЕЙ ФИН · EVOLVING CASCADE NEURAL NETWORK BASED ON MULTIDIMESNIONAL EPANECHNIKOV’S ... · APPLICATION OF DISCRETE OPTIMIZATION IN SOLVING A PROBLEM ... · AN ALGORITHM FOR FRESNEL DIFFRACTION COMPUTING BASED ON FRACTIONAL ... · DYNAMICAL SYSTEMS IN DESCRIPTION OF NONLINEAR RECURSIVE ... ·
I.2.6 Learning
article: A STUDY OF APPLICATION OF NEURAL NETWORK TECHNIQUE ON SOFTWARE REPOSITORIES · SEMANTIC NET FROM CONCEPTS AS A MODEL OF STUDENT’S KNOWLEDGE: HOW STABLE ARE ... · МЕТОД ПОИСКА РЕШЕНИЙ В ИНТЕЛЛЕКТУАЛЬНЫХ СИСТЕМАХ ПОДДЕРЖКИ ПРИНЯТИЯ РЕШЕНИЙ ... · THE MODEL FOR THE COMBINED CASCADE RADIAL BASIS NEURAL NETWORK AND ITS ... · DIDACTIC DESIGNING OF RESOURCE SUPPORT FOR TRAINING ENVIRONMENT · КОМПЛЕКСНЫЙ АНАЛИЗ РИСКА БАНКРОТСТВА КОРПОРАЦИЙ В УСЛОВИЯХ НЕОПРЕДЕЛЕННОСТИ · IMPROVING ACTIVE RULES PERFORMANCE IN NEW P SYSTEM COMMUNICATION ARCHITECTURES · SOFTWARE EFFORT ESTIMATION USING RADIAL BASIS FUNCTION NEURAL NETWORKS · CONCEPTUAL KNOWLEDGE MODELING ON THE BASIS OF NATURAL CLASSIFICATION · A COMPUTER METHOD TO STUDY THE ENTIRETY OF STUDENTS’ KNOWLEDGE ACQUIRED DURING A · INTELLIGENT TRADING SYSTEMS · MODELING OF COGNITIVE PROCESSES BY NETWORK MODELS · ADAPTIVE FUZZY PROBABILISTIC CLUSTERING OF INCOMPLETE DATA · Polynomial Regression using a Perceptron with Axo-axonic Connections · RESERVOIR FORECASTING NEURO-FUZZY NETWORK AND ITS LEARNING · MODELING OF COGNITIVE PROCESSES BY NETWORK MODELS · POLYNOMIAL APPROXIMATION USING PARTICLE SWARM OPTIMIZATION OF LINEAR ... · ФОРМИРОВАНИЕ БАЗОВЫХ СТРУКТУР ВОСПРИЯТИЯ И · DECISIONS ON SELECTING THE TRAINING ALGORITHM OF THE NEURAL NETWORK WITH ... · ОБУЧЕНИЕ РЕКУРРЕНТНЫХ НЕЙРОННЫХ СЕТЕЙ МЕТО · ЧИСЛЕННЫЕ МЕРЫ “СПЛОЧЕННОСТИ” ИМЕННЫХ ГРУ · ADAPTIVE CLUSTERING OF INCOMPLETE DATA USING NEURO-FUZZY KOHONEN NETWORK · INTELLIGENT ANALYSIS OF MARKETING DATA · STUDY THE QUALITY OF GLOBAL NEURAL MODEL WITH REGARD TO LOCAL MODELS OF ... · HYBRID CASCADE NEURAL NETWORK BASED ON WAVELET-NEURON · ARTIFICIAL INTELLIGENCE IN MONITORING SYSTEM · TACIT KNOWLEDGE AS A RESOURCE FOR ORGANIZATIONS AND ITS INTENSITY IN VARIOUS ... · THE E-LEARNING SYSTEM WITH EMBEDDED NEURAL NETWORK · ИССЛЕДОВАНИЕ МНОГОКРИТЕРИАЛЬНОЙ ЗАДАЧИ ОП� · ЭКСПЕРИМЕНТАЛЬНОЕ ИЗУЧЕНИЕ ЦЕЛОСТНОСТИ ЗН� · SELECTIVE EVOLUTION CONTROL METHOD FOR EVOLUTION STRATEGIES WITH NEURAL ... · EVOLVING CASCADE NEURAL NETWORK BASED ON MULTIDIMESNIONAL EPANECHNIKOV’S ... · ADAPTIVE NEURO-FUZZY KOHONEN NETWORK WITH VARIABLE FUZZIFIER · CONCEPTUAL KNOWLEDGE MODELING AND SYSTEMATIZATION ON THE BASIS OF NATURAL ... · ON COORDINATION OF EXPERTS’ ESTIMATIONS OF QUANTITATIVE VARIABLE∗ · THE CASCADE NEO-FUZZY ARCHITECTURE AND ITS ONLINE LEARNING ALGORITHM · THE CASCADE GROWING NEURAL NETWORK USING QUADRATIC NEURONS AND ITS LEARNING ... · EDUKIT: INFO-EDUCATIONAL PLATFORM ENABLING TO CREATE WEBSITES FOR SECONDARY ... · SYSTEMOLOGICAL CLASSIFICATION ANALYSIS IN CONCEPTUAL KNOWLEDGE MODELING · ANALOGIES BETWEEN TEXTS: MATHEMATICAL MODELS AND APPLICATIONS IN ... · HYBRID SYSTEMS OF COMPUTATIONAL INTELLIGENCE EVOLVED FROM SELFLEARNING ... · THE CASCADE NEO-FUZZY ARCHITECTURE USING CUBIC–SPKINE ACTIVATION FUNCTIONS · ADAPTIVE COMPARTMENTAL WAVELON WITH ROBUST LEARNING ALGORITHM · THE CASCADE ORTHOGONAL NEURAL NETWORK · OUTLIERS RESISTANT LEARNING ALGORITHM FOR RADIAL-BASIS-FUZZY-WAVELET-NEURAL ... · MULTIDIMENSIONAL HETEROGENEOUS VARIABLE PREDICTION ... · THE CASCADE GROWING NEURAL NETWORK USING QUADRATIC NEURONS ... · ADAPTIVE GUSTAFSON-KESSEL FUZZY CLUSTERING ALGORITHM BASED ON ... · SEARCHING FOR NEAREST STRINGS WITH NEURAL-LIKE STRING EMBEDDING · MEASURE REFUTATIONS AND METRICS ON STATEMENTS OF EXPERTS ... · GROWING NEURAL NETWORKS USING NONCONVENTIONAL ACTIVATION FUNCTIONS · CONSTRUCTING OF A CONSENSUS OF SEVERAL EXPERTS STATEMENTS∗ · DECISION TREES FOR APPLICABILITY OF EVOLUTION RULES IN TRANSITION P SYSTEMS · APPROACHES TO SEQUENCE SIMILARITY REPRESENTATION · NEURAL NETWORK BASED APPROACH FOR DEVELOPING THE ENTERPRISE STRATEGY · ANALOGOUS REASONING AND CASE-BASED REASONING FOR INTELLIGENT ... · USING SENSITIVITY AS A METHOD FOR RANKING THE TEST CASES CLASSIFIED ... · DIAGARA: AN INCREMENTAL ALGORITHM FOR INFERRING IMPLICATIVE RULES FROM EXAMPLES · A NEW APPROACH FOR ELIMINATING THE SPURIOUS STATES ... · ADAPTIVE WAVELET-NEURO-FUZZY NETWORK IN THE FORECASTING ... ·
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