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Rule Based Systems for Big Data - A Machine Learning Approach (Hardcover, 1st ed. 2015): Han Liu, Alexander Gegov, Mihaela Cocea Rule Based Systems for Big Data - A Machine Learning Approach (Hardcover, 1st ed. 2015)
Han Liu, Alexander Gegov, Mihaela Cocea
R3,708 R3,426 Discovery Miles 34 260 Save R282 (8%) Ships in 12 - 19 working days

The ideas introduced in this book explore the relationships among rule based systems, machine learning and big data. Rule based systems are seen as a special type of expert systems, which can be built by using expert knowledge or learning from real data. The book focuses on the development and evaluation of rule based systems in terms of accuracy, efficiency and interpretability. In particular, a unified framework for building rule based systems, which consists of the operations of rule generation, rule simplification and rule representation, is presented. Each of these operations is detailed using specific methods or techniques. In addition, this book also presents some ensemble learning frameworks for building ensemble rule based systems.

Flow Modelling and Control in Pipeline Systems - A Formal Systematic Approach (Hardcover, 1st ed. 2021): Sina Razvarz, Raheleh... Flow Modelling and Control in Pipeline Systems - A Formal Systematic Approach (Hardcover, 1st ed. 2021)
Sina Razvarz, Raheleh Jafari, Alexander Gegov
R2,880 Discovery Miles 28 800 Ships in 10 - 15 working days

This book introduces novel methods for leak and blockage detection in pipelines. The leak happens as a result of ageing pipelines or extreme pressure forced by operational error or valve rapid variation. Many factors influence blockage formation in pipes like wax deposition that leads to the formation and eventual growth of solid layers and deposition of suspended solid particles in the fluids. In this book, initially, different categories of leak detection are overviewed. Afterwards, the observability and controllability of pipeline systems are analysed. Control variables can be usually presented by pressure and flow rates at the start and end points of the pipe. Different cases are considered based on the selection of control variables to model the system. Several theorems are presented to test the observability and controllability of the system. In this book, the leakage flow in the pipelines is studied numerically to find the relationship between leakage flow and pressure difference. Removing leakage completely is almost impossible; hence, the development of a formal systematic leakage control policy is the most reliable approach to reducing leakage rates.

Fuzzy Networks for Complex Systems - A Modular Rule Base Approach (Hardcover, Edition.): Alexander Gegov Fuzzy Networks for Complex Systems - A Modular Rule Base Approach (Hardcover, Edition.)
Alexander Gegov
R4,393 Discovery Miles 43 930 Ships in 10 - 15 working days

This book introduces the novel concept of a fuzzy network whose nodes are rule bases and the connections between the nodes are the interactions between the rule bases in the form of outputs fed as inputs. The concept is presented as a systematic study for improving the feasibility and transparency of fuzzy models by means of modular rule bases whereby the model accuracy and efficiency can be optimised in a flexible way. The study uses an effective approach for fuzzy rule based modelling of complex systems that are characterised by attributes such as nonlinearity, uncertainty, dimensionality and structure.The approach is illustrated by formal models for fuzzy networks, basic and advanced operations on network nodes, properties of operations, feedforward and feedback fuzzy networks as well as evaluation of fuzzy networks. The results are demonstrated by numerous examples, two case studies and software programmes within the Matlab environment that implement some of the theoretical methods from the book. The book shows the novel concept of a fuzzy network with networked rule bases as a bridge between the existing concepts of a standard fuzzy system with a single rule base and a hierarchical fuzzy system with multiple rule bases.

Complexity Management in Fuzzy Systems - A Rule Base Compression Approach (Hardcover, 2007 ed.): Alexander Gegov Complexity Management in Fuzzy Systems - A Rule Base Compression Approach (Hardcover, 2007 ed.)
Alexander Gegov
R2,924 Discovery Miles 29 240 Ships in 10 - 15 working days

This book presents a systematic study on the inherent complexity in fuzzy systems, resulting from the large number and the poor transparency of the fuzzy rules. The study uses a novel approach for complexity management, aimed at compressing the fuzzy rule base by removing the redundancy while preserving the solution. The compression is based on formal methods for presentation, manipulation, transformation and simplification of fuzzy rule bases.

Distributed Fuzzy Control of Multivariable Systems (Hardcover, 1996 ed.): Alexander Gegov Distributed Fuzzy Control of Multivariable Systems (Hardcover, 1996 ed.)
Alexander Gegov
R2,987 Discovery Miles 29 870 Ships in 10 - 15 working days

It is known that many control processes are characterized by both quantitative and qualitative complexity. Tbe quantitative complexity is usually expressed in a large number of state variables, respectively high dimensional mathematical model. Tbe qualitative complexity is usually associated with uncertain behaviour, respectively approximately known mathematical model. If the above two aspects of complexity are considered separately, the corresponding control problem can be easily solved. On one hand, large scale systems theory has existed for more than 20 years and has proved its capabilities in solving high dimensional control problems on the basis of decomposition, hierarchy, decentralization and multilayers. On the other hand, the fuzzy linguistic approach is almost at the same age and has shown its advantages in solving approximately formulated control problems on the basis of linguistic reasoning and logical inference. However, if both aspects of complexity are considered together, the corresponding control problem becomes non-trivial and does not have an easy solution. Modem control theory and practice have reacted accordingly to the above mentioned new cballenges of tbe day by utilizing the latest achievements in computer technology and artificial intelligence distributed computation and intelligent operation. In this respect, a new field has emerged in the last decade, called " Distributed intelligent control systems" . However, the majority of the familiar works in this field are still either on an empirical or on a conceptual level and this is a significant drawback.

Flow Modelling and Control in Pipeline Systems - A Formal Systematic Approach (Paperback, 1st ed. 2021): Sina Razvarz, Raheleh... Flow Modelling and Control in Pipeline Systems - A Formal Systematic Approach (Paperback, 1st ed. 2021)
Sina Razvarz, Raheleh Jafari, Alexander Gegov
R2,849 Discovery Miles 28 490 Ships in 10 - 15 working days

This book introduces novel methods for leak and blockage detection in pipelines. The leak happens as a result of ageing pipelines or extreme pressure forced by operational error or valve rapid variation. Many factors influence blockage formation in pipes like wax deposition that leads to the formation and eventual growth of solid layers and deposition of suspended solid particles in the fluids. In this book, initially, different categories of leak detection are overviewed. Afterwards, the observability and controllability of pipeline systems are analysed. Control variables can be usually presented by pressure and flow rates at the start and end points of the pipe. Different cases are considered based on the selection of control variables to model the system. Several theorems are presented to test the observability and controllability of the system. In this book, the leakage flow in the pipelines is studied numerically to find the relationship between leakage flow and pressure difference. Removing leakage completely is almost impossible; hence, the development of a formal systematic leakage control policy is the most reliable approach to reducing leakage rates.

Advances in Computational Intelligence Systems - Contributions Presented at the 19th UK Workshop on Computational Intelligence,... Advances in Computational Intelligence Systems - Contributions Presented at the 19th UK Workshop on Computational Intelligence, September 4-6, 2019, Portsmouth, UK (Paperback, 1st ed. 2020)
Zhaojie Ju, Longzhi Yang, Chenguang Yang, Alexander Gegov, Dalin Zhou
R4,429 Discovery Miles 44 290 Ships in 10 - 15 working days

This book highlights the latest research in computational intelligence and its applications. It covers both conventional and trending approaches in individual chapters on Fuzzy Systems, Intelligence in Robotics, Deep Learning Approaches, Optimization and Classification, Detection, Inference and Prediction, Hybrid Methods, Emerging Intelligence, Intelligent Health Care, and Engineering Data- and Model-Driven Applications. All chapters are based on peer-reviewed contributions presented at the 19th Annual UK Workshop on Computational Intelligence, held in Portsmouth, UK, on 4-6 September 2019. The book offers a valuable reference guide for readers with expertise in computational intelligence or who are seeking a comprehensive and timely review of the latest trends in computational intelligence. Special emphasis is placed on novel methods and their use in a wide range of application areas, updating both academics and professionals on the state of the art.

Advances in Computational Intelligence Systems - Contributions Presented at the 18th UK Workshop on Computational Intelligence,... Advances in Computational Intelligence Systems - Contributions Presented at the 18th UK Workshop on Computational Intelligence, September 5-7, 2018, Nottingham, UK (Paperback, 1st ed. 2019)
Ahmad Lotfi, Hamid Bouchachia, Alexander Gegov, Caroline Langensiepen, Martin McGinnity
R5,468 Discovery Miles 54 680 Ships in 10 - 15 working days

This book presents the latest trends in and approaches to computational intelligence research and its application to intelligent systems. It covers a long list of interconnected research areas, such as fuzzy systems, neural networks, evolutionary computation, clustering and classification, machine learning, data mining, cognition and robotics, and deep learning. The individual chapters are based on peer-reviewed contributions presented at the 18th Annual UK Workshop on Computational Intelligence (UKCI-2018), held in Nottingham, UK on September 5-7, 2018. The book puts a special emphasis on novel methods and reports on their use in a wide range of applications areas, thus providing both academics and professionals with a comprehensive and timely overview of new trends in computational intelligence.

Rule Based Systems for Big Data - A Machine Learning Approach (Paperback, Softcover reprint of the original 1st ed. 2016): Han... Rule Based Systems for Big Data - A Machine Learning Approach (Paperback, Softcover reprint of the original 1st ed. 2016)
Han Liu, Alexander Gegov, Mihaela Cocea
R3,212 Discovery Miles 32 120 Ships in 10 - 15 working days

The ideas introduced in this book explore the relationships among rule based systems, machine learning and big data. Rule based systems are seen as a special type of expert systems, which can be built by using expert knowledge or learning from real data. The book focuses on the development and evaluation of rule based systems in terms of accuracy, efficiency and interpretability. In particular, a unified framework for building rule based systems, which consists of the operations of rule generation, rule simplification and rule representation, is presented. Each of these operations is detailed using specific methods or techniques. In addition, this book also presents some ensemble learning frameworks for building ensemble rule based systems.

Advances in Computational Intelligence Systems - Contributions Presented at the 16th UK Workshop on Computational Intelligence,... Advances in Computational Intelligence Systems - Contributions Presented at the 16th UK Workshop on Computational Intelligence, September 7-9, 2016, Lancaster, UK (Paperback, 1st ed. 2017)
Plamen Angelov, Alexander Gegov, Chrisina Jayne, Qiang Shen
R7,018 Discovery Miles 70 180 Ships in 10 - 15 working days

The book is a timely report on advanced methods and applications of computational intelligence systems. It covers a long list of interconnected research areas, such as fuzzy systems, neural networks, evolutionary computation, evolving systems and machine learning. The individual chapters are based on peer-reviewed contributions presented at the 16th Annual UK Workshop on Computational Intelligence, held on September 7-9, 2016, in Lancaster, UK. The book puts a special emphasis on novels methods and reports on their use in a wide range of applications areas, thus providing both academics and professionals with a comprehensive and timely overview of new trends in computational intelligence.

Fuzzy Networks for Complex Systems - A Modular Rule Base Approach (Paperback, 2011 ed.): Alexander Gegov Fuzzy Networks for Complex Systems - A Modular Rule Base Approach (Paperback, 2011 ed.)
Alexander Gegov
R4,351 Discovery Miles 43 510 Ships in 10 - 15 working days

This book introduces the novel concept of a fuzzy network whose nodes are rule bases and the connections between the nodes are the interactions between the rule bases in the form of outputs fed as inputs. The concept is presented as a systematic study for improving the feasibility and transparency of fuzzy models by means of modular rule bases whereby the model accuracy and efficiency can be optimised in a flexible way. The study uses an effective approach for fuzzy rule based modelling of complex systems that are characterised by attributes such as nonlinearity, uncertainty, dimensionality and structure.The approach is illustrated by formal models for fuzzy networks, basic and advanced operations on network nodes, properties of operations, feedforward and feedback fuzzy networks as well as evaluation of fuzzy networks. The results are demonstrated by numerous examples, two case studies and software programmes within the Matlab environment that implement some of the theoretical methods from the book. The book shows the novel concept of a fuzzy network with networked rule bases as a bridge between the existing concepts of a standard fuzzy system with a single rule base and a hierarchical fuzzy system with multiple rule bases.

Complexity Management in Fuzzy Systems - A Rule Base Compression Approach (Paperback, Softcover reprint of hardcover 1st ed.... Complexity Management in Fuzzy Systems - A Rule Base Compression Approach (Paperback, Softcover reprint of hardcover 1st ed. 2007)
Alexander Gegov
R2,895 Discovery Miles 28 950 Ships in 10 - 15 working days

This book presents a systematic study on the inherent complexity in fuzzy systems, resulting from the large number and the poor transparency of the fuzzy rules. The study uses a novel approach for complexity management, aimed at compressing the fuzzy rule base by removing the redundancy while preserving the solution. The compression is based on formal methods for presentation, manipulation, transformation and simplification of fuzzy rule bases.

Distributed Fuzzy Control of Multivariable Systems (Paperback, Softcover reprint of hardcover 1st ed. 1996): Alexander Gegov Distributed Fuzzy Control of Multivariable Systems (Paperback, Softcover reprint of hardcover 1st ed. 1996)
Alexander Gegov
R2,873 Discovery Miles 28 730 Ships in 10 - 15 working days

It is known that many control processes are characterized by both quantitative and qualitative complexity. Tbe quantitative complexity is usually expressed in a large number of state variables, respectively high dimensional mathematical model. Tbe qualitative complexity is usually associated with uncertain behaviour, respectively approximately known mathematical model. If the above two aspects of complexity are considered separately, the corresponding control problem can be easily solved. On one hand, large scale systems theory has existed for more than 20 years and has proved its capabilities in solving high dimensional control problems on the basis of decomposition, hierarchy, decentralization and multilayers. On the other hand, the fuzzy linguistic approach is almost at the same age and has shown its advantages in solving approximately formulated control problems on the basis of linguistic reasoning and logical inference. However, if both aspects of complexity are considered together, the corresponding control problem becomes non-trivial and does not have an easy solution. Modem control theory and practice have reacted accordingly to the above mentioned new cballenges of tbe day by utilizing the latest achievements in computer technology and artificial intelligence distributed computation and intelligent operation. In this respect, a new field has emerged in the last decade, called " Distributed intelligent control systems" . However, the majority of the familiar works in this field are still either on an empirical or on a conceptual level and this is a significant drawback.

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