Displaying similar documents to “Transport Modeling: an Artificial Immune System Approach”

Adaptive control of cluster-based Web systems using neuro-fuzzy models

Krzysztof Zatwarnicki (2012)

International Journal of Applied Mathematics and Computer Science

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A significant development of Web technologies requires the application of more and more complex systems and algorithms for maintaining high quality of Web services. Presently, not only simple decision-making tools but also complex adaptation algorithms using artificial intelligence techniques are applied for controlling HTTP request traffic. The paper presents a new LFNRD (Local Fuzzy-Neural Adaptive Request Distribution) algorithm for request distribution in cluster-based Web systems...

A model of route lifetime optimization with linguistic knowledge in wireless ad-hoc networks.

E. Natsheh, S. Khatun, A. Jantan (2006)

Mathware and Soft Computing

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Ad-hoc On-Demand Distance Vector (AODV) routing protocol has been and continues to be a very active and fruitful research protocol since its introduction in the wireless ad-hoc networks. AODV uses a static value for its route lifetime parameter called Active Route Timeout (ART) which indicates the time that the route can stay active in the routing table. Route lifetime may be more accurately determined dynamically via measurement, instead of static value. To accomplish this, the fuzzy...

Visual anomaly detection via soft computing: a prototype application at NASA.

Jesús A. Domínguez, Steven J. Klinko (2003)

Mathware and Soft Computing

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A visual system prototype that detects anomalies or defects in real time under normal lighting operating conditions was built for NASA at the Kennedy Space Center (KSC). The system prototype is basically a learning machine that integrates the three elements of soft computing, Fuzzy Logic (FL), Artificial Neural Network (ANN), and Genetic Algorithm (GA) schemes to process the image, run the learning process, and finally detect the anomalies or defects. The system acquires the image, performs...

Learning under hardware restrictions in CMOS fuzzy controllers able to extract rules from examples.

Fernando Vidal Verdú, Rafael Navas-González, Angel Rodríguez-Vázquez (1996)

Mathware and Soft Computing

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Fuzzy controllers are able to incorporate knowledge expressed in if-then rules. These rules are given by experts or skilful operators. Problems arise when there are no experts or/and rules are not easy to find. Author's proposal consists on an analog fuzzy controller which accepts structured language as well as input/output data pairs, thus rules can be extracted or tuned from human or software controller operation. Learning from data pairs has to be carried out under hardware restrictions...

Some practical problems in fuzzy sets-based decision support systems.

Alejandro Sancho-Royo, José Luis Verdegay, Edmundo Vergara-Moreno (1999)

Mathware and Soft Computing

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In this paper some problems arising in the interface between two different areas, Decision Support Systems and Fuzzy Sets and Systems, are considered. The Model-Base Management System of a Decision Support System which involves some fuzziness is considered, and in that context the question, first, of the practical determination of membership functions, second of the management of the fuzziness in some optimisation models, and finally of using fuzzy rules for terminating conventional...

A neuro-fuzzy system for sequence alignment on two levels.

Tillman Weyde, Klaus Dalinghaus (2004)

Mathware and Soft Computing

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The similarity judgerment of two sequences is often decomposed in similarity judgements of the sequence events with an alignment process. However, in some domains like speech or music, sequences have an internal structure which is important for intelligent processing like similarity judgements. In an alignment task, this structure can be reflected more appropriately by using two levels instead of aligning event by event. This idea is related to the structural alignment framework by Markman...