Throughout the years, different applications show a growing complexity in fields like optimization, learning or modeling. Under these circumstances, traditional approaches lack from the required properties to solve these problems appropriately. Fortunately, researchers and engineers have been able to overcome these difficulties by applying more sophisticated methodologies. Among all techniques,...

Much is unknown about intelligence, and much will remain beyond human comprehension. The fundamental nature of intelligence is only poorly understood and even the definition of intelligence remains a subject of controversy. Considerable research is currently being devoted to an understanding and a representation of intelligence. According to a dictionary, intelligence means the ability to compr...

In this chapter, we present a brief overview of bioinformatics and computational intelligence (CI) methods including artificial neural networks, genetic algorithms, and fuzzy systems. A number of representative applications of CI methods in bioinformatics are discussed, including CI methods for gene expression analysis, for multiple sequence alignment, for protein-protein interaction prediction...

There are two complementary views of artificial intelligence (AI): one as an engineering discipline concerned with the creation of intelligent machines, the other as an empirical science concerned with the computational modeling of human intelligence. When the field was young, these two views were seldom distinguished. Since then, a substantial divide has opened up, with the former view dominat...

Smart grid integrates advanced sensing technologies, control methodologies, and communication technologies into current electricity grid at transmission and distribution levels in order to supply electricity in a smart, user friendly way. Smart grid encourages integration of renewable energy sources, distributed generation, and plug-in hybrid and electric vehicles in distributed power systems, ...

Type-1 Fuzzy Logic Systems (FLSs) have been applied to date with great success to different applications. However, for many real-world applications, there is a need to cope with large amounts of uncertainties. The traditional Type-1 FLSs that use crisp Type-1 fuzzy sets cannot directly handle such uncertainties. Type-2 FLSs that use Type2 fuzzy sets can handle such uncertainties to produce a be...

The term Artificial Immune Systems (AIS) refers to a class of computational algorithms that are inspired by processes apparent in the natural immune system. As such, they belong to a wider family of biologically inspired algorithms such as evolutionary algorithms, ant-colony algorithms and other swarm inspired algorithms for example. The natural immune system can in the simplest case be viewed ...

We give a brief introduction to computational intelligence application in medicine. We review medical image processing in magnetic resonance images and nondestructive evaluation studies by ultrasonic systems. Primary processes of medical image processing are segmentation, registration and enhancement. In them, automated segmentation is received much considerable attentions. In general, several ...

Since the early 1990s the field of Evolutionary Computation has experienced a tremendous growth of interest resulting in many new ideas, new algorithms and new applications. This growth is both a blessing and a curse. It serves as strong evidence of the usefulness of these techniques, but makes it difficult to see “the big picture” regarding how the many instances of evolutionary algorithms rel...

Here are some problems to help you understand the material in Computational Intelligence: A Logical Approach. They are designed to help students understand the material and practice for exams. This file is available in html, or in pdf format, either without solutions or with solutions. (The pdf can be read using the free acrobat reader or with recent versions of Ghostscript). Given the knowledg...