This special issue encompasses eight papers devoted to the recent developments in the field of Data Mining. The issue originated from presentations of the special issue “Soft Computing Techniques in Data Mining” at “10th Internacional Conference on Intelligent Data Engineering and Automated Learning (IDEAL 09)” held in Burgos (Spain), September 23–26th, 2009, together with invited papers from w...

This article presents a study of academic performance evaluation using soft computing techniques inspired by the successful application of K-means, fuzzy C-means (FCM), subtractive clustering (SC), hybrid subtractive clustering-fuzzy C-means (SC-FCM) and hybrid subtractive clustering-adaptive neuro fuzzy inference system (SC-ANFIS) methods for solving academic performance evaluation problems. M...

This paper presents the implementation of soft computing (SC) techniques in the field of natural language processing. An attempt is made to design and implement an automatic tagger that extract a free text and then tag it. The part of speech taggers (POS) is the process of categorization words based on their meaning, functions and types (noun, verb, adjective, etc). Two stages tagging system ba...

This paper presents methods and tools which can be used within the framework of diagnostics and prognostics to accommodate imprecision of real systems. We outline the advantages and disadvantages of the different techniques and show how they can be used in a hybrid fashion to complement each other. We conclude the paper with a number of successful real world examples.

A Manufacturing Execution System (MES) consists of high-cost, large-scale, multi-task software systems. Companies and factories apply these complex applications for the purposes of production management to monitor and track all aspects of factory-based manufacturing processes. Nevertheless, companies seek to control the production process with even greater rigour. Improvements associated with a...

This volume is about knowledge processing with interval and soft computing, i.e., about techniques that use both interval and soft computing to process knowledge and about the results of applying these techniques. To better understand these techniques, in Chapter 1, we described fundamentals of interval computing, and in Chapter 2, we described the fundamentals of soft computing. Now it is time...

Soft Computing models play an important role in the field of recognition, classification, data prediction, etc in various application fields. Soft Computing models include fuzzy logic, neural, network, genetic algorithm, particle swarm optimization, Bacterial forging algotithm, classification and clustering, etc., the extraction of hidden information from large database is possible through the ...

nowadays, groundwater resources play a vital role as a source of drinking water in arid and semiarid regions and forecasting of pollutants content in these resources is very important. therefore, this study aimed to compare two soft computing methods for modeling cd, pb and zn concentration in groundwater resources of asadabad plain, western iran. the relative accuracy of several soft computing...

With the rapid advancement in the field of Information Technology Software organizations are trying to use the strength of various emerging and powerful techniques such as Soft Computing techniques to develop/produce software products at minimum cost with maximum quality in terms of reliability, portability, accessibility, maintainability etc. In fact Soft Computing techniques and its impact as...

car-following models, as the most popular microscopic traffic flow modeling, is increasingly being used by transportation experts to evaluate new intelligent transportation system (its) applications. a number of factors including individual differences of age, gender, and risk-taking behavior, have been found to influence car-following behavior. this paper presents a novel idea to calculate the...