9 resultados para Programming environments
em SAPIENTIA - Universidade do Algarve - Portugal
Resumo:
In the field of control systems it is common to use techniques based on model adaptation to carry out control for plants for which mathematical analysis may be intricate. Increasing interest in biologically inspired learning algorithms for control techniques such as Artificial Neural Networks and Fuzzy Systems is in progress. In this line, this paper gives a perspective on the quality of results given by two different biologically connected learning algorithms for the design of B-spline neural networks (BNN) and fuzzy systems (FS). One approach used is the Genetic Programming (GP) for BNN design and the other is the Bacterial Evolutionary Algorithm (BEA) applied for fuzzy rule extraction. Also, the facility to incorporate a multi-objective approach to the GP algorithm is outlined, enabling the designer to obtain models more adequate for their intended use.
Resumo:
The design phase of B-spline neural networks is a highly computationally complex task. Existent heuristics have been found to be highly dependent on the initial conditions employed. Increasing interest in biologically inspired learning algorithms for control techniques such as Artificial Neural Networks and Fuzzy Systems is in progress. In this paper, the Bacterial Programming approach is presented, which is based on the replication of the microbial evolution phenomenon. This technique produces an efficient topology search, obtaining additionally more consistent solutions.
Resumo:
The design phase of B-spline neural networks represents a very high computational task. For this purpose, heuristics have been developed, but have been shown to be dependent on the initial conditions employed. In this paper a new technique, Bacterial Programming, is proposed, whose principles are based on the replication of the microbial evolution phenomenon. The performance of this approach is illustrated and compared with existing alternatives.
Resumo:
Discrete optimization problems are very difficult to solve, even if the dimantion is small. For most of them the problem of finding an ε-approximate solution is already NP-hard.
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In this work we develop a methodology for the economic evaluation of soil tillage technologies, in a risky environment, and to capture the influence of farmer behaviour on his technology choice. The model has short-term activities, that change with the type of year, and long-term activities, in which sets of traction investment activities are included. Although these activities do not change with the type of year, they lead to different availability of resources for each type of year, since the same tractor has different available fieldwork days under different weather conditions. We prove that the model is sensitive to the greater income variability resulting from the use of alternative technologies and to the balance between income and risk, accounting for the probability of occurrence of each state of nature and giving an investment solution that considers the best production plan for each type of year. (c) 2005 Elsevier B.V. All rights reserved.
Resumo:
Vehicular networking is a new field that is expected to be widely adopted in the near future. One of the key applications inherent to this novel communications paradigm is content delivery to on-board users. In this paper we focus specifically on broadcast-based content delivery. We propose a content delivery scheme that is optimized for performance in order to improve the maximum amount of data than can be delivered, while also reducing delivery time to a minimum. With this goal our study combines both analytical and simulation results to determine the optimal packet size for content delivery so as to achieve the maximum throughput possible at different distances, and considering both static and mobile receivers. Experimental results show that our optimizations provide efficient delivery of multimedia contents for distances up to 200 meters when relying on IEEE 802.lip based broadcasting. Copyright © 2010 ACM.
Resumo:
Dissertação de mestrado, Biologia Marinha, Faculdade de Ciências e Tecnologia, Universidade do Algarve, 2015
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Tese de doutoramento, Ciências da Vida, do Mar, da Terra e do Ambiente (Nutrição), Faculdade de Ciências e Tecnologia, Universidade do Algarve, 2015
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Dissertação de Mestrado, Biologia Marinha, Faculdade de Ciências e Tecnologia, Universidade do Algarve, 2015