SpringerBriefs in Computational Intelligence

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 proposed …

The language of business is the language of dreams, but the language of war is the language of nightmare made real. Yet business dreams of driverless cars on intelligent roads, and of other real-time critical systems under the control of …

This Brief presents a study of SAX/GA, an algorithm to optimize market trading strategies, to understand how the sequential implementation of SAX/GA and genetic operators work to optimize possible solutions. This study is later used as the …

In this book a new model for data classification was developed. This new model is based on the competitive neural network Learning Vector Quantization (LVQ) and type-2 fuzzy logic. This computational model consists of the hybridization of the …

In this book, a methodology for parameter adaptation in meta-heuristic op-timization methods is proposed. This methodology is based on using met-rics about the population of the meta-heuristic methods, to decide through a fuzzy inference system …

In this book, a series of granular algorithms are proposed. A nature inspired granular algorithm based on Newtonian gravitational forces is proposed. A series of methods for the formation of higher-type information granules represented by Interval …

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. Proposing a power and throughput-aware …

Artificial Intelligence is a huge breakthrough technology that is changing our world. It requires some degrees of technical skills to be developed and understood, so in this book we are going to first of all define AI and categorize it with a …

In this book four new methods are proposed. In the first method the generalized type-2 fuzzy logic is combined with the morphological gra-dient technique. The second method combines the general type-2 fuzzy systems (GT2 FSs) and the Sobel …

This book focuses on the fields of fuzzy logic, bio-inspired algorithm; especially bee colony optimization algorithm and also considering the fuzzy control area. The main idea is that this areas together can to solve various control problems and …

This book focuses on the fields of fuzzy logic, granular computing and also considering the control area. These areas can work together to solve various control problems, the idea is that this combination of areas would enable even more complex pr

The work in this book is based on philosophical as well as logical views on the subject of decoding the ‘progress’ of decision making process in the cognition system of a decision maker (be it a human or an animal or a bird or any livi

This work presents a new approach to portfolio composition in the stock market. It incorporates a fundamental approach using financial ratios and technical indicators with a Multi-Objective Evolutionary Algorithms to choose the portfolio composition

In this book, a new method for hybrid intelligent systems is proposed. The proposed method is based on a granular computing approach applied in two levels. The techniques used and combined in the proposed method are modular neural networks (MNNs) …

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 …

This brief provides a detailed introduction, discussion and bibliographic review of the nature1-inspired optimization algorithm called Harmony Search. It uses a large number of simulation results to demonstrate the advantages of Harmony Search and it

This work addresses the research and development of an innovative optimization kernel applied to analog integrated circuit (IC) design. Particularly, this works describes the modifications inside the AIDA Framework, an electronic design automation fr

This book introduces a variety of neural network methods for solving differential equations arising in science and engineering. The emphasis is placed on a deep understanding of the neural network techniques, which has been presented in a mostly h

This book proposes a novel approach for time-series prediction using machine learning techniques with automatic feature generation. Application of machine learning techniques to predict time-series continues to attract considerable attention due to t

This book applies to the scientific area of electronic design automation (EDA) and addresses the automatic sizing of analog integrated circuits (ICs). Particularly, this book presents an approach to enhance a state-of-the-art layout-aware circuit-lev