In multi-agent systems, most of the time, an agent does not have complete information about the preferences and decision making processes of other agents. This prevents even the cooperative agents from making coordinated choices, purely due to their ignorance of what others want. To overcome this problem, traditional coordination methods rely heavily on inter-agent communication, and thus becom...

Many renewable energy resources like windturbines or solar collectors are volatile and unstable. Distributed energy producing entities are clustered to virtual power plants that – from a black-box perspective – should act like conventional stable power plants. It is the task of intelligent control strategies to compensate fluctuations and to exploit renewable recourses to a maximal extend. In t...

A classifier is a central reasoning component of modern knowledge representation systems. Classifiers provide such fundamental intelligent services as concept categorization, instance recognition, and query processing. Unfortunately, as the size of the knowledge base grows, classifiers become less useful because the classifier must process a significant fraction of the knowledge base to perform...

Control charts primarily in the form of X chart are widely used to identify the situations when control actions will be needed for manufacturing systems. Various types of patterns are observed in control charts. Identification of these control chart patterns (CCPs) can provide clues to potential quality problems in the manufacturing process. This paper introduces a novel hybrid intelligent syst...

Various classification techniques have been developed for the classification of protein sequences using feature selection method. Feature selection is important in accurate classification. This paper discussed some popular methods that involve feature selection for precise classification of protein sequences such as neural network based classifier, fuzzy method based classifier and rough set ba...

This paper presents an efficient algorithm for the classification of features into strong and weak features for every distinct subject to create an intelligent online signature verification system. Whereas Euclidean distance classifier is used for validation processes and low error rates obtained illustrate the feasibility of the algorithm for an online signature verification system. Keywords-S...

This paper describes classification of typed student utterances within AutoTutor, an intelligent tutoring system. Utterances are classified to one of 18 categories, including 16 question categories. The classifier presented uses part of speech tagging, cascaded finite state transducers, and simple disambiguation rules. Shallow NLP is well suited to the task: session log file analysis reveals si...

Motivated by the amount of code that goes unidentified on the web, we introduce a practical method for algorithmically identifying the programming language of source code. Our work is based on supervised learning and intelligent statistical features. We also explored, but abandoned, a grammatical approach. In testing, our implementation greatly outperforms that of an existing tool that relies o...

Nowadays, as information systems are more open to the Internet, the importance of secure networks is tremendously increased. New intelligent Intrusion Detection Systems (IDSs) which are based on sophisticated algorithms rather than current signature-base detections are in demand. In this paper, we propose a new data-mining based technique for intrusion detection using an ensemble of binary clas...

The Self-Organizing Incremental Neural Network (SOINN) is an unsupervised classifier that is capable of online incremental learning. Studies have been performed not only for improving the SOINN, but also for applying it to various problems. Furthermore, using the SOINN, more intelligent functions are achieved, such as association, reasoning, and so on. In this paper, we show how to use the SOIN...