Bøger i SpringerBriefs in Computational Intelligence serien

This open access book serves as a compact source of information on sine cosine algorithm (SCA) and a foundation for developing and advancing SCA and its applications. SCA is an easy, user-friendly, and strong candidate in the field of metaheuristics algorithms. Despite being a relatively new metaheuristic algorithm, it has achieved widespread acceptance among researchers due to its easy implementation and robust optimization capabilities. Its effectiveness and advantages have been demonstrated in various applications ranging from machine learning, engineering design, and wireless sensor network to environmental modeling. The book provides a comprehensive account of the SCA, including details of the underlying ideas, the modified versions, various applications, and a working MATLAB code for the basic SCA.

This book aims to critically assess the Cartesian stance that affirms robotic and AI technologies as candidates to supplant human capacities in non-routine intellectual nature activities based on social power relations. In the argumentation listed, the contradictions that this hypothesis approaches will be exposed, mainly in a historical and social analysis based on a complex and uncertain sociological perspective, added by a discussion within the scope of the Chaos theory. Finally, an outline of the current era, fostered by extremisms and extremists, will be described in terms of its contradictions in an attempt at sociological analysis. For this, some crucial and unsettling questions will be asked, and an effort to come up with answers will be made for some.

It also helps find ways in which we can measure possible consequences and societal impacts by taking the following factors into account: open public health issues and common AI solutions (with multiple case studies, such as TB and SARS: COVID-19), AI in sustainable health care, AI in precision medicine and data privacy issues.

This book presents different experimental results as evidence of the good results obtained compared with respect to conventional approaches and literature references based on fuzzy logic. The main objective of the present work is the generation of fuzzy diagnosis systems that offer competitive classifiers to be applied in diagnosis systems.

This book emphasizes that learning efficiency of the learners can be increased by providing personalized course materials and guiding them to attune with suitable learning paths based on their characteristics such as learning style, knowledge level, emotion, motivation, self-efficacy and many more learning ability factors in e-learning system.

This book presents a methodology for forecasting events and phenomena occurring in technology and natural environments. The methodology helps determining the time of the onset of a destructive earthquake, its strength and the coordinates of the epicentre, predicting the time of the descent of glaciers and landslides long before the event.

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.

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.

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.

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.

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.

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.

The new approach was implement-ed as a hybrid intelligent system combining modular neural net-works and fuzzy systems. Finally, two genetic algo-rithms are used to perform the optimization of the modular neural networks parameters and fuzzy inference system parameters.

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'.

This book introduces a variety of neural network methods for solving differential equations arising in science and engineering.

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