Implementación de Redes Neuro-Difusas Para Per Aplicadas en Problemas de Clasificación Y Modelización

Implementación de Redes Neuro-Difusas Para Per Aplicadas en Problemas de Clasificación Y Modelización PDF Author: José D. Martín
Publisher: Universal-Publishers
ISBN: 158112113X
Category : Psychology
Languages : en
Pages : 113

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Book Description
Se analiza el uso de redes neuro-difusas para solucionar problemas de clasificación y modelización. El objetivo es intentar combinar las cualidades de las redes neuronales y de la descripción de sistemas mediante Lógica Difusa. Las redes neuronales son conocidas por su alta capacidad de aprendizaje, lo que permite una adecuada generalización en el tipo de problemas comentado anteriormente. Su aplicación a problemas reales no ha dejado de crecer durante los últimos años. Por otro lado, la Lógica Difusa es una herramienta más novedosa, cuya propiedad más atractiva es la capacidad que posee de poder tratar con variables numéricas y variables lingüísticas simultáneamente. Las variables lingüísticas permiten un tratamiento del problema más comprensible y cercano al conocimiento intuitivo humano. Una de las principales ventajas de la combinación de estas disciplinas es la posibilidad de interpretar los resultados obtenidos por una red neuronal, pudiendo extraer conocimiento de ella. Clásicamente, las redes neuronales han sido conocidas como sistemas que podían proporcionar excelentes resultados pero que tenían el principal inconveniente de ser cajas negras, de donde era imposible obtener unas reglas de comportamiento debido a la complejidad de sus conexiones internas. De esta manera, la Lógica Difusa abre una puerta a esta posibilidad. (Complete work in Spanish) The use of Neuro-Fuzzy Networks is analysed for solving classification and modelisation problems. The objective is to combine the properties of Neural Networks with the systems' description by using Fuzzy Logic. The ability of learning of Neural Networks implies a good generalisation features. Their application to real problems has grown during the last years. On the other hand, Fuzzy Logic is a recent tool, whose most attractive property is the ability for working with numeric and linguistic variables simultanously. Linguistic variables allow the user to treat problems in a more understandable way since they are near to human knowledge. One of the main advantages of the proposed combination is the possibility of interpreting the results obtained by Neural Networks since we can extract information of Neural Networks by using Fuzzy Logic. This information will be estructured in fuzzy rules of the type "If-Then". Typically, Neural Networks have been known as systems capable to get excellent results but with the main drawback of their black-box behaviour. Thus, it was impossible to extract rules of their behaviour or learning because of the complex internal connections. Fuzzy Logic offers a feasible exit for this problem.

Implementación de Redes Neuro-Difusas Para Per Aplicadas en Problemas de Clasificación Y Modelización

Implementación de Redes Neuro-Difusas Para Per Aplicadas en Problemas de Clasificación Y Modelización PDF Author: José D. Martín
Publisher: Universal-Publishers
ISBN: 158112113X
Category : Psychology
Languages : en
Pages : 113

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Book Description
Se analiza el uso de redes neuro-difusas para solucionar problemas de clasificación y modelización. El objetivo es intentar combinar las cualidades de las redes neuronales y de la descripción de sistemas mediante Lógica Difusa. Las redes neuronales son conocidas por su alta capacidad de aprendizaje, lo que permite una adecuada generalización en el tipo de problemas comentado anteriormente. Su aplicación a problemas reales no ha dejado de crecer durante los últimos años. Por otro lado, la Lógica Difusa es una herramienta más novedosa, cuya propiedad más atractiva es la capacidad que posee de poder tratar con variables numéricas y variables lingüísticas simultáneamente. Las variables lingüísticas permiten un tratamiento del problema más comprensible y cercano al conocimiento intuitivo humano. Una de las principales ventajas de la combinación de estas disciplinas es la posibilidad de interpretar los resultados obtenidos por una red neuronal, pudiendo extraer conocimiento de ella. Clásicamente, las redes neuronales han sido conocidas como sistemas que podían proporcionar excelentes resultados pero que tenían el principal inconveniente de ser cajas negras, de donde era imposible obtener unas reglas de comportamiento debido a la complejidad de sus conexiones internas. De esta manera, la Lógica Difusa abre una puerta a esta posibilidad. (Complete work in Spanish) The use of Neuro-Fuzzy Networks is analysed for solving classification and modelisation problems. The objective is to combine the properties of Neural Networks with the systems' description by using Fuzzy Logic. The ability of learning of Neural Networks implies a good generalisation features. Their application to real problems has grown during the last years. On the other hand, Fuzzy Logic is a recent tool, whose most attractive property is the ability for working with numeric and linguistic variables simultanously. Linguistic variables allow the user to treat problems in a more understandable way since they are near to human knowledge. One of the main advantages of the proposed combination is the possibility of interpreting the results obtained by Neural Networks since we can extract information of Neural Networks by using Fuzzy Logic. This information will be estructured in fuzzy rules of the type "If-Then". Typically, Neural Networks have been known as systems capable to get excellent results but with the main drawback of their black-box behaviour. Thus, it was impossible to extract rules of their behaviour or learning because of the complex internal connections. Fuzzy Logic offers a feasible exit for this problem.

Aplicación de un modelo de red neuronal no supervisado a la clasificación de consumidores eléctricos

Aplicación de un modelo de red neuronal no supervisado a la clasificación de consumidores eléctricos PDF Author: Sergio Valero Verdú
Publisher: Editorial Club Universitario
ISBN: 8415787065
Category : Technology & Engineering
Languages : es
Pages : 166

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Book Description
El libro muestra la capacidad de las redes neuronales y en concreto de los mapas auto-organizados de Teuvo Kohonen, los conocidos como Self-Organizing Maps (SOM) para clasificar consumidores eléctricos a partir de históricos de datos reales de consumo. El espectro de datos de entrada está formado por más de 20 tipos de consumidores distintos de una misma región geográfica. La red neuronal SOM ha demostrado ser una eficaz herramienta para segmentar y clasificar consumidores a partir de sus perfiles de carga diarios y ha permitido identificar nuevos consumidores, no utilizados antes para entrenar el mapa. Esta identificación posterior y la asignación automática a un segmento o clúster de clientes permiten asociar nuevos consumidores a patrones de consumo previamente clasificados. Este procedimiento permitiría a compañías comercializadoras y a clientes conocer a partir de los datos de consumo diario a qué cluster de consumidores pertenece y elegir tarifas específicas en función del patrón de consumo de este grupo.

Time Series Prediction

Time Series Prediction PDF Author: Andreas S. Weigend
Publisher: Routledge
ISBN: 042997227X
Category : Social Science
Languages : en
Pages : 665

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Book Description
The book is a summary of a time series forecasting competition that was held a number of years ago. It aims to provide a snapshot of the range of new techniques that are used to study time series, both as a reference for experts and as a guide for novices.

Fault Diagnosis

Fault Diagnosis PDF Author: Józef Korbicz
Publisher: Springer Science & Business Media
ISBN: 3642186157
Category : Computers
Languages : en
Pages : 936

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Book Description
This comprehensive work presents the status and likely development of fault diagnosis, an emerging discipline of modern control engineering. It covers fundamentals of model-based fault diagnosis in a wide context, providing a good introduction to the theoretical foundation and many basic approaches of fault detection.

Cloud Computing, Big Data & Emerging Topics

Cloud Computing, Big Data & Emerging Topics PDF Author: Marcelo Naiouf
Publisher: Springer
ISBN: 9783030848248
Category : Computers
Languages : en
Pages : 203

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Book Description
This book constitutes the revised selected papers of the 9th International Conference on Cloud Computing, Big Data & Emerging Topics, JCC-BD&ET 2021, held in La Plata, Argentina*, in June 2021. The 12 full papers and 2 short papers presented were carefully reviewed and selected from a total of 37 submissions. The papers are organized in topical sections on parallel and distributed computing; machine and deep learning; big data; web and mobile computing; visualization.. *The conference was held virtually due to the COVID-19 pandemic.

Solar Drying Technology

Solar Drying Technology PDF Author: Om Prakash
Publisher: Springer
ISBN: 9811038333
Category : Technology & Engineering
Languages : en
Pages : 640

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Book Description
This book offers a comprehensive reference guide to the latest developments and advances in solar drying technology, covering the concept, design, testing, modeling, and economics of solar drying technologies, as well as their impact on the environment. The respective chapters are based on the latest studies conducted by reputed international researchers in the fields of solar energy and solar drying. Offering a perfect blend of research and practice explained in a simple manner, the book represents a valuable resource for researchers, students, professionals, and policymakers working in the field of solar drying and related agricultural applications.

Handbook of Research on Metaheuristics for Order Picking Optimization in Warehouses to Smart Cities

Handbook of Research on Metaheuristics for Order Picking Optimization in Warehouses to Smart Cities PDF Author: Ochoa Ortiz-Zezzatti, Alberto
Publisher: IGI Global
ISBN: 1522581324
Category : Business & Economics
Languages : en
Pages : 498

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Book Description
Building accurate algorithms for the optimization of picking orders is a difficult task, especially when one considers the delays of real-world situations. In warehouse environments, diverse algorithms must be developed to enhance the global performance relating to combining customer orders into picking orders to reduce wait times. The Handbook of Research on Metaheuristics for Order Picking Optimization in Warehouses to Smart Cities is a pivotal reference source that addresses strategies for developing able algorithms in order to build better picking orders and the impact of these strategies on the picking systems in which diverse algorithms are implemented. While highlighting topics such ABC optimization, environmental intelligence, and order batching, this publication examines common picking aspects in warehouse environments ranging from manual order picking systems to automated retrieval systems. This book is intended for researchers, teachers, engineers, managers, and practitioners seeking research on algorithms to enhance the order picking performance.

Applied Biomechatronics Using Mathematical Models

Applied Biomechatronics Using Mathematical Models PDF Author: Jorge Garza Ulloa
Publisher: Academic Press
ISBN: 0128125950
Category : Technology & Engineering
Languages : en
Pages : 662

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Book Description
Applied Biomechatronics Using Mathematical Models provides an appropriate methodology to detect and measure diseases and injuries relating to human kinematics and kinetics. It features mathematical models that, when applied to engineering principles and techniques in the medical field, can be used in assistive devices that work with bodily signals. The use of data in the kinematics and kinetics analysis of the human body, including musculoskeletal kinetics and joints and their relationship to the central nervous system (CNS) is covered, helping users understand how the complex network of symbiotic systems in the skeletal and muscular system work together to allow movement controlled by the CNS. With the use of appropriate electronic sensors at specific areas connected to bio-instruments, we can obtain enough information to create a mathematical model for assistive devices by analyzing the kinematics and kinetics of the human body. The mathematical models developed in this book can provide more effective devices for use in aiding and improving the function of the body in relation to a variety of injuries and diseases. Focuses on the mathematical modeling of human kinematics and kinetics Teaches users how to obtain faster results with these mathematical models Includes a companion website with additional content that presents MATLAB examples

Phosphorus in Environmental Technology

Phosphorus in Environmental Technology PDF Author: E. Valsami-Jones
Publisher: IWA Publishing
ISBN: 1843390019
Category : Science
Languages : en
Pages : 681

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Book Description
Phosphorus in Environmental Technology: Principles and Applications, provides a definitive and detailed presentation of state-of-the-art knowledge on the environmental behaviour of phosphorus and its applications to the treatment of waters and soils. Special attention is given to phosphorus removal for recovery technologies, a concept that has emerged over the past 5-6 years. The book features an all-encompassing approach: the fundamental science of phosphorus (chemistry, geochemistry, mineralogy, biology), key aspects of its environmental behaviour and mobility, industrial applications (treatment, removal, recovery) and the principles behind such applications, novel biotechnologies and, importantly, it also addresses socio-economic issues which often influence implementation and the ultimate success of any new technology. A detailed subject index helps the reader to find their way through the different scientific and technological aspects covered, making it an invaluable reference work for students, professionals and consultants dealing with phosphorus-related environmental technologies. State-of-the-art knowledge on the behaviour of phosphorus and its applications to environmental science and technology. Covers all aspects of phosphorus in the environment, engineered and biological systems; an interdisciplinary text.

Applied Biomedical Engineering Using Artificial Intelligence and Cognitive Models

Applied Biomedical Engineering Using Artificial Intelligence and Cognitive Models PDF Author: Jorge Garza Ulloa
Publisher: Elsevier
ISBN: 0128209348
Category : Science
Languages : en
Pages : 705

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Book Description
Applied Biomedical Engineering Using Artificial Intelligence and Cognitive Models focuses on the relationship between three different multidisciplinary branches of engineering: Biomedical Engineering, Cognitive Science and Computer Science through Artificial Intelligence models. These models will be used to study how the nervous system and musculoskeletal system obey movement orders from the brain, as well as the mental processes of the information during cognition when injuries and neurologic diseases are present in the human body. The interaction between these three areas are studied in this book with the objective of obtaining AI models on injuries and neurologic diseases of the human body, studying diseases of the brain, spine and the nerves that connect them with the musculoskeletal system. There are more than 600 diseases of the nervous system, including brain tumors, epilepsy, Parkinson's disease, stroke, and many others. These diseases affect the human cognitive system that sends orders from the central nervous system (CNS) through the peripheral nervous systems (PNS) to do tasks using the musculoskeletal system. These actions can be detected by many Bioinstruments (Biomedical Instruments) and cognitive device data, allowing us to apply AI using Machine Learning-Deep Learning-Cognitive Computing models through algorithms to analyze, detect, classify, and forecast the process of various illnesses, diseases, and injuries of the human body. Applied Biomedical Engineering Using Artificial Intelligence and Cognitive Models provides readers with the study of injuries, illness, and neurological diseases of the human body through Artificial Intelligence using Machine Learning (ML), Deep Learning (DL) and Cognitive Computing (CC) models based on algorithms developed with MATLAB® and IBM Watson®. Provides an introduction to Cognitive science, cognitive computing and human cognitive relation to help in the solution of AI Biomedical engineering problems Explain different Artificial Intelligence (AI) including evolutionary algorithms to emulate natural evolution, reinforced learning, Artificial Neural Network (ANN) type and cognitive learning and to obtain many AI models for Biomedical Engineering problems Includes coverage of the evolution Artificial Intelligence through Machine Learning (ML), Deep Learning (DL), Cognitive Computing (CC) using MATLAB® as a programming language with many add-on MATLAB® toolboxes, and AI based commercial products cloud services as: IBM (Cognitive Computing, IBM Watson®, IBM Watson Studio®, IBM Watson Studio Visual Recognition®), and others Provides the necessary tools to accelerate obtaining results for the analysis of injuries, illness, and neurologic diseases that can be detected through the static, kinetics and kinematics, and natural body language data and medical imaging techniques applying AI using ML-DL-CC algorithms with the objective of obtaining appropriate conclusions to create solutions that improve the quality of life of patients