Download or read book Neuro fuzzy Methods in Cognitive Systems of Monitoring and Forecasting of Scientific and Technological Development of the Country written by and published by . This book was released on 2015 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Abstract: On the basis of many national and international research a neural network model of the trajectory of and techno-economic development, which allows to calculate the level and rate of fuel and energy is developed and the method of evaluating the effectiveness of technological innovation projects on a range of qualitative and quantitative parameters based on the construction of the neuro-fuzzy solution tree is proposed. The developed model, in addition to the promising project choosing, explains the decision making process in an understandable way, in the structure of the neuro-diagnostic decision rules "If ... then." Thus, this technique allows to determine the significance of the indicators (trends) of the formation of new technological cycles and to identify the reference parameters of the social dimension of the economy. Data received as a result of the intellectual analysis can be used by experts to assess the efficiency of the automated calculation of the effectiveness of technology projects in order to predict the scientific and technological development of the country and make necessary recommendations to the political and socio-economic spheres. Research results can be used both by private and public companies and organizations. This will help to assess and predict future changes, give proper recommendations to scientific institutions in key areas: such as security and counter-terrorism; living systems; nanosystem and materials Industry, information and telecommunication systems, advanced weapons, military and special equipment, management natural resources, transport, aviation and space systems, energy and energy efficiency.

Download or read book Cognitive Systems for Monitoring and Forecasting the Scientific and Technological Development of the State written by T.V. Abramova and published by Red Square Scientific, Ltd.. This book was released on 2018 with total page 253 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book INTELLECTUAL MULTI LEVEL SYSTEM FOR NEURO FUZZY AND COGNITIVE ANALYSIS AND FORECAST OF SCIENTIFIC TECHNOLOGICAL AND INNOVATIVE DEVELOPMENT written by Sergey Gorbachev and published by Infinite Study. This book was released on with total page 9 pages. Available in PDF, EPUB and Kindle. Book excerpt: The article is devoted to description of structure and operation algorithms of a multilevel intellectual system for analysis and forecast of scientific-technological and innovative development of objects and territories based on expert methods, trainable models of fuzzy logic and fuzzy cognitive analysis. The article analyses distinctions and advantages of the system in making forecast evaluation and scenarios of the dynamics of multidimensional feature objects and processes. The authors have built a neutrosophic cognitive map for interaction of technologies based on the results of foresight studies.

Download or read book Design of Fuzzy Cognitive Model of Mutual Influence and Connectivity of Innovative Technologies written by Sergey Gorbachev and published by Infinite Study. This book was released on with total page 7 pages. Available in PDF, EPUB and Kindle. Book excerpt: The article is devoted to research and development of fuzzy cognitive model of mutual influence and connectivity of innovative technologies on the basis of synthesis of interdisciplinary research strategies -foresight methods based on logically transparent mechanisms of interpretation of the solution, expert weighting methods and neutrosophic cognitive maps. Neutrosophic cognitive map of mutual influence and connectivity of innovative technologies is constructed on the basis of data on the nature and intensity of these interactions, allowing to calculate the degree of influence of one or several concepts (technologies), taking into account their state, on the target indicator, and also calculate the fixed state of the concept system. The results of experimental verification and the multiplicative effect of the developed model on the data of expert surveys are described, under conditions of transition to the 6th technological order.

Download or read book Fuzzy and Neuro Fuzzy Intelligent Systems written by Ernest Czogała and published by Springer Science & Business Media. This book was released on 2000-04-06 with total page 220 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book provides an introduction to basic concepts as well as some recent advancements in fuzzy set theory, approximate reasoning, artificial neural networks and clustering methods. These methodologies create together the so-called soft computing, which is part of a computational approach to system intelligence. The book deals with an overview of fuzzy set theory, foundations for approximate reasoning principles, specific equivalence of inference results using logical conjunctive interpretations of if-then rules, supervised and unsupervised artificial neural networks, a new generalized conditional fuzzy clustering method, artificial neural networks-based fuzzy inference system with parameterized consequences in if-then rules, MATLAB(R) m-files implementation of neuro-fuzzy systems, detailed study of neuro-fuzzy systems applications.

Download or read book Fuzzy Cognitive Maps for Applied Sciences and Engineering written by Elpiniki I. Papageorgiou and published by Springer Science & Business Media. This book was released on 2013-12-02 with total page 411 pages. Available in PDF, EPUB and Kindle. Book excerpt: Fuzzy Cognitive Maps (FCM) constitute cognitive models in the form of fuzzy directed graphs consisting of two basic elements: the nodes, which basically correspond to “concepts” bearing different states of activation depending on the knowledge they represent, and the “edges” denoting the causal effects that each source node exercises on the receiving concept expressed through weights. Weights take values in the interval [-1,1], which denotes the positive, negative or neutral causal relationship between two concepts. An FCM can be typically obtained through linguistic terms, inherent to fuzzy systems, but with a structure similar to the neural networks, which facilitates data processing, and has capabilities for training and adaptation. During the last 10 years, an exponential growth of published papers in FCMs was followed showing great impact potential. Different FCM structures and learning schemes have been developed, while numerous studies report their use in many contexts with highly successful modeling results. The aim of this book is to fill the existing gap in the literature concerning fundamentals, models, extensions and learning algorithms for FCMs in knowledge engineering. It comprehensively covers the state-of-the-art FCM modeling and learning methods, with algorithms, codes and software tools, and provides a set of applications that demonstrate their various usages in applied sciences and engineering.

Download or read book Neuro fuzzy bsp hierarchical system for time forecasting and fuzzy rule extraction dor data mining applicatons written by and published by . This book was released on 2000 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Esta dissertação investiga a utilização de um sistema Neuro-Fuzzy Hierárquico para previsão de séries e a extração de regras fuzzy em aplicações de Mineração de Dados. O objetivo do trabalho foi estender o modelo Neuro-Fuzzy Hierárquico BSP para a classificação de registros e a previsão de séries temporais. O processo de classificação de registros no contexto de Mineração de Dados consiste na extração de regras de associação que melhor caracterizem, através de sua acurácia e abrangência, um determinado grupo de registros de um banco de dados (BD). A previsão de séries temporais, outra tarefa comum em Mineração de Dados tem como objetivo prever o comportamento de uma série temporal no instante t+k (k? 1).O trabalho consistiu de 5 etapas principais: elaborar um survey dos principais sistemas e modelos mais utilizados nas aplicações de Mineração de Dados; avaliar o desempenho do sistema NFHB original em aplicações de Mineração de Dados; desenvolver uma extensão do modelo NFHB dedicado à classificação de registros em uma BD; desenvolver um novo modelo híbrido Neuro-Fuzzy Genético para o ajuste automático dos parâmetros do sistema dedicado a previsão de séries temporais; e o estudo dos casos. O estudo da área resultou num survey sobre os principais modelos para Mineração de Dados. São apresentados os modelos mais utilizados em tarefas de classificação e extração de regras tais como: redes neurais, árvores de decisão crisp e fuzzy, algoritmos genéticos, estatística e sistemas neuro-fuzzy. Na etapa de avaliação do modelo NFHB original, foi verificado que além do tradicional aprendizado dos parâmetros, comuns às redes neurais e aos sistemas neuro-fuzzy, o modelo possui as seguintes aracterísticas: aprendizado da estrutura, a partir do uso de particionamentos recursivos; número maior de entradas que o habitualmente encontrado nos sistemas neuro-fuzzy; e regras com hierarquia, características adequadas para as aplicações de Mineração de Dados. Entretanto, o processo de extração de regras e a seleção de atributos não são adequados para este tipo de aplicação, assim como a excessiva complexidade da parametrização do modelo para aplicações de previsão de séries temporais. Uma extensão ao modelo NFHB original foi então proposta para aplicações de classificação de registros no contexto da Mineração de Dados onde se têm como objetivo principal a extração de informação em forma de regras interpretáveis. Foi necessário modificar a seleção de atributos e o processo original de extração de regras. O sistema fuzzy do tipo Takagi-Sugeno do modelo NFHB original fornece regras inadequadas do ponto de vista da Mineração de Dados. O novo modelo NFHB, dotado das modificações necessárias, mostrou um ótimo desempenho na extração de regras fuzzy válidas que descrevem a informação contida no banco de dados. As medidas de avaliação normalmente usadas para analisar regras crisp (Se x1 é

Download or read book Evolving Neuro fuzzy Tools for System Classification and Prediction written by Josip Jr Vrbanek and published by . This book was released on 2008 with total page 194 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Classification and prediction algorithims have recently become very powerful tools to a wide array of real-world applications. Some real world applications include system condition monitoring, bioinformatics, robotics, predictive control, earthquake prediction, weather forecasting, stock market and traffic pattern prediction, just to name a few. Within this work, several novel approaches, as well as modifications to some existing approaches, are introduced in order to improve the performance of current classification and prediction paradigms. In the first section of this work, a novel weighted recurrent neuro-fuzzy inference system is introduced alongside two existing neural networks. It is found that the novel design outperforms both the existing neural networks in terms of equal-step and sequential-step inputs for time-series forecasting. The second contribution of this work is the development of a novel evolving clustering algorithim for classification and prediction. This particular algorithim starts without any priori knowledge of the distribution of the data set. The novel design is capable of revealing the true cluster configuration in a single pass of the data, estimating the location and variance of each cluster. After a rigorous performance evaluation, it is found that the novel design outperforms many existing clustering approaches including the well-known potential-based evolving Takagi-Sugeno (eTS) clustering scheme. The third and fourth contributions of this work are the development of a second novel clustering technique and a novel hybrid training technique. The clustering technique is a combination of the aforementioned scheme and the potential-based technique. The new training algorithm is a combination of the decoupled-extended Kalman filter (for the backward pass) and the recursive least-sequares estimate (for the forward pass). It is found that the novel clustering technique outperforms many available clustering techniques. Also, the novel training algorithm is proven to outperform most existing training techniques."--Abstract.

Download or read book Neuro Fuzzy Techniques for Intelligent Information Systems written by Nikola K. Kasabov and published by Physica. This book was released on 1999-03-29 with total page 472 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume comprises selected chapters that cover contemporary issues of the development and the application of neuro-fuzzy techniques. Developing and using neural networks, fuzzy logic systems, genetic algorithms and statistical methods as separate techniques, or in their combination, have been research topics in several areas such as mathematics, engineering, computer science, physics, economics and finance. Here the latest results in the fields are presented from both theoretical and practical point of view. The volume has four main parts. Part one presents generic techniques and theoretical issues while part two, three and four deal with practically oriented models, systems and implementations.

Download or read book Fuzzy and Neuro Fuzzy Intelligent Systems written by Ernest Czogala and published by . This book was released on 2000-04-06 with total page 212 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Tracing Chains of Thought written by Benjoe A. Juliano and published by Physica. This book was released on 1996-04-04 with total page 256 pages. Available in PDF, EPUB and Kindle. Book excerpt: We always seem to be comparing various conceptual structures in many of our higher mental activities. In any case, we use similarities and discrepancies in forming all our conceptual categories. In this book, the authors present a computerized approach to diagnosis: in particular, cognitive diagnosis. It uses fuzzy graph structures called fuzzy cognitive maps (FCMs). These are used in an attempt to model the intriacies of the higher mental processes. The area of structure comparison, focusing on measures of similarity and discrepancy, is also dealt with. A very interesting aspect of the book is how the authors approached the problem of cognitive diagnosis using fuzzy techniques. Some connections and differences from other approaches are also covered. The reader will find this book both informative and interesting.

Download or read book Neural Fuzzy Systems written by Ching Tai Lin and published by . This book was released on 1996 with total page 797 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Development of A Self Organizing Neuro Fuzzy System for Application to System Modeling and Forecasting written by 翁梓程 and published by . This book was released on 2009 with total page 70 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Converging Technologies for Improving Human Performance written by Mihail C. Roco and published by Springer Science & Business Media. This book was released on 2013-04-17 with total page 477 pages. Available in PDF, EPUB and Kindle. Book excerpt: M. C. Roco and W.S. Bainbridge In the early decades of the 21st century, concentrated efforts can unify science based on the unity of nature, thereby advancing the combination of nanotechnology, biotechnology, information technology, and new technologies based in cognitive science. With proper attention to ethical issues and societal needs, converging in human abilities, societal technologies could achieve a tremendous improvement outcomes, the nation's productivity, and the quality of life. This is a broad, cross cutting, emerging and timely opportunity of interest to individuals, society and humanity in the long term. The phrase "convergent technologies" refers to the synergistic combination of four major "NBIC" (nano-bio-info-cogno) provinces of science and technology, each of which is currently progressing at a rapid rate: (a) nanoscience and nanotechnology; (b) biotechnology and biomedicine, including genetic engineering; (c) information technology, including advanced computing and communications; (d) cognitive science, including cognitive neuroscience. Timely and Broad Opportunity. Convergence of diverse technologies is based on material unity at the nanoscale and on technology integration from that scale.

Download or read book Neuro fuzzy Based Intelligent Approaches to Nonlinear System Identification and Forecasting written by Abeer Alshejari and published by . This book was released on 2018 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Neural Fuzzy Control Systems with Structure Parameter Learning written by Ching Tai Lin and published by . This book was released on 1994 with total page 127 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book 13th International Conference on Theory and Application of Fuzzy Systems and Soft Computing ICAFS 2018 written by Rafik A. Aliev and published by Springer. This book was released on 2018-12-28 with total page 970 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the proceedings of the 13th International Conference on Application of Fuzzy Systems and Soft Computing (ICAFS 2018), held in Warsaw, Poland on August 27–28, 2018. It includes contributions from diverse areas of soft computing such as uncertain computation, Z-information processing, neuro-fuzzy approaches, evolutionary computing and others. The topics of the papers include theory of uncertainty computation; theory and application of soft computing; decision theory with imperfect information; neuro-fuzzy technology; image processing with soft computing; intelligent control; machine learning; fuzzy logic in data analytics and data mining; evolutionary computing; chaotic systems; soft computing in business, economics and finance; fuzzy logic and soft computing in the earth sciences; fuzzy logic and soft computing in engineering; soft computing in medicine, biomedical engineering and the pharmaceutical sciences; and probabilistic and statistical reasoning in the social and educational sciences. The book covers new ideas from theoretical and practical perspectives in economics, business, industry, education, medicine, the earth sciences and other fields. In addition to promoting the development and application of soft computing methods in various real-life fields, it offers a useful guide for academics, practitioners, and graduates in fuzzy logic and soft computing fields.