Bøger i SpringerBriefs in Computational Intelligence serien

Thanks to recent advances in sensors, communication and satellite technology, data storage, processing and networking capabilities, satellite image acquisition and mining are now on the rise.

As a client or a developer, what do you need to consider when developing an age-appropriate website or mobile application? This book explains how age-related limitations affect the use of websites and mobile applications. If gerontological aspects are not taken into account in the design of digital channels, older people tend to do without them. Therefore, websites and mobile applications need to take into account the needs of older people. In the book, you will find useful recommendations on how to do this so that your websites and mobile apps are easy to use for everyone.

This book presents the basics of the Laser Assisted Oxygen (LASOX) cutting process, its development, advantages and shortcomings, together with detailed information on the research work carried out to date regarding the modelling and optimization of the process.

This book presents a proposal for a new soft computing innovative method called by "CFE" forevaluation of the football matches of FIFA(IFAB) and UEFA to compute the true 'Winner'.

In addition to the above, the book provides detailed analysis of iris images and two methods of iris segmentation. It also discusses simplified study of some subspace-based methods and distance measures for iris recognition backed by empirical studies and statistical success verifications.

The management of financial portfolios or funds constitutes a widely known problematic in financial markets which normally requires a rigorous analysis in order to select the most profitable assets. This book proposes a potential system based on Genetic Algorithms, which aims to manage a financial portfolio by using technical analysis indicators.

This book presents an innovative methodology for the automatic generation of analog integrated circuits (ICs) layout, based on template descriptions and on evolutionary computational techniques.

This book presents a new computational finance approach combining a Symbolic Aggregate approximation (SAX) technique with an optimization kernel based on genetic algorithms (GA).

Recent advancements in machine learning, neuroscience, and artificial intelligence technology will be addressed, and new business models introduced for and by artificial intelligence research will be analyzed.

In this book a neural network learning method with type-2 fuzzy weight adjustment is proposed. The mathematical analysis of the proposed learning method architecture and the adaptation of type-2 fuzzy weights are presented. The proposed method is based on research of recent methods that handle weight adaptation and especially fuzzy weights.The internal operation of the neuron is changed to work with two internal calculations for the activation function to obtain two results as outputs of the proposed method. Simulation results and a comparative study among monolithic neural networks, neural network with type-1 fuzzy weights and neural network with type-2 fuzzy weights are presented to illustrate the advantages of the proposed method.The proposed approach is based on recent methods that handle adaptation of weights using fuzzy logic of type-1 and type-2. The proposed approach is applied to a cases of prediction for the Mackey-Glass (for ├┤=17) and Dow-Jones time series, and recognition of person with iris biometric measure. In some experiments, noise was applied in different levels to the test data of the Mackey-Glass time series for showing that the type-2 fuzzy backpropagation approach obtains better behavior and tolerance to noise than the other methods.The optimization algorithms that were used are the genetic algorithm and the particle swarm optimization algorithm and the purpose of applying these methods was to find the optimal type-2 fuzzy inference systems for the neural network with type-2 fuzzy weights that permit to obtain the lowest prediction error.

This book proposes a novel approach for time-series prediction using machine learning techniques with automatic feature generation. The proposed method can be applied to a wide range of machine learning architectures and applications to represent complex feature dependencies explicitly when machine learning cannot achieve this by itself.

This is the first book to focus on solving cooperative control problems of multiple robot arms using different centralized or distributed neural network models, presenting methods and algorithms together with the corresponding theoretical analysis and simulated examples.

This book focuses on identifying the performance challenges involved in computer architectures, optimal configuration settings and analysing their impact on the performance of multi-core architectures.

The techniquesused and combined in the proposed method are modular neural networks (MNNs)with a Granular Computing (GrC) approach, thus resulting in a new concept ofMNNs;

This book examines how the wonders of AI have contributed to the battle against COVID-19.

The book describes various texture feature extraction approaches and texture analysis applications. It introduces and discusses the importance of texture features, and describes various types of texture features like statistical, structural, signal-processed and model-based.

Whenfuzzy logic is used it make it easy to performed the simulations, these fuzzysystems help to model the behavior of a real systems, using the fuzzysystems fuzzy rules are generated and with this can generate the behavior ofany variable depending on the inputs and linguistic value.

This book examines the intelligent random walk algorithms based on learning automata: these versions of random walk algorithms gradually obtain required information from the nature of the application to improve their efficiency.

A combination of several technological, healthcare and financial factors are driving this trend to create a new healthcare model that stresses preventative 'health-care' rather than 'sick-care', and a shift from volume to value.

For this reason we consider in this book the proposed method using fuzzy systems, fuzzy controllers, and bee colony optimization algorithm improve the behavior of the complex control problems.

This book focuses on the fields of fuzzy logic and metaheuristic algorithms, particularly the harmony search algorithm and fuzzy control. There are currently several types of metaheuristics used to solve a range of real-world of problems, and these metaheuristics contain parameters that are usually fixed throughout the iterations. However, a number of techniques are also available that dynamically adjust the parameters of an algorithm, such as probabilistic fuzzy logic.This book proposes a method of addressing the problem of parameter adaptation in the original harmony search algorithm using type-1, interval type-2 and generalized type-2 fuzzy logic. The authors applied this methodology to the resolution of problems of classical benchmark mathematical functions, CEC 2015, CEC2017 functions and to the optimization of various fuzzy logic control cases, and tested the method using six benchmark control problems ¿ four of the Mamdani type: the problem of filling a water tank, theproblem of controlling the temperature of a shower, the problem of controlling the trajectory of an autonomous mobile robot and the problem of controlling the speed of an engine; and two of the Sugeno type: the problem of controlling the balance of a bar and ball, and the problem of controlling control the balance of an inverted pendulum. When the interval type-2 fuzzy logic system is used to model the behavior of the systems, the results show better stabilization because the uncertainty analysis is better. As such, the authors conclude that the proposed method, based on fuzzy systems, fuzzy controllers and the harmony search optimization algorithm, improves the behavior of complex control plants.

The language of business is the language of dreams, but the language of war is the language of nightmare made real.

In this book a new model for data classification was developed. Some architectures were developed in order to work mainly with two datasets, an arrhythmia dataset (using ECG signals) for classifying 15 different types of arrhythmias, and a satellite images segments dataset used for classifying six different types of soil.

Focusing on the mathematical computation of the uncertain behavior of evacuees, which is switching action behavior, it subsequently reproduces the crowd evacuation process under several conjectural scenarios using a DEM-based multi-agent model that has been modified by introducing the switching action behavior.

This book discusses in detail the latest trends in sentiment analysis,focusing on "how online reviews and feedback reflect the opinions of users and have led to a major shift in the decision-making process at organizations." Social networking has become essential in today's society.

This book describes a new pattern discovery approach based on the combination among rules between Perceptually Important Points (PIPs) and the Symbolic Aggregate approximation (SAX) representation optimized by Genetic Algorithm (GA).

The asymptotic limit theorems of control and information theories make it possible to explore the dynamics of collapse likely to afflict large-scale systems of autonomous ground vehicles that communicate with each other and with an embedding intelligent roadway.

A series of methods for the formation of higher-type information granules represented by Interval Type-2 Fuzzy Sets are also shown, via multiple approaches, such as Coefficient of Variation, principle of justifiable granularity, uncertainty-based information concept, and numerical evidence based.