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Showing 1 to 9 of 9 for “"Multi-Objective Optimization (MOO)"”.
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Multi-objective optimization techniques in electricity generation planning
The objective of this research is to develop a framework of multi-objective optimization (MOO) models that are better capable of providing decision support on future long-term electricity generation planning (EGP), in the context of insufficient electricity capacity and to apply it to the …
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Modelling, simulation and multi-objective optimization of industrial hydrocrackers
… and achieve the best resource utilization. Multiple objectives are relevant in such cases. The availability of powerful computational resources and robust evolutionary techniques like Genetic Algorithm (GA), have led to a revolution in the field of multi-objective optimization (MOO). This …
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Evolutionary Optimization of Neural Architectures for Remaining Useful Life Prediction
… accuracy. On the other side, we consider multi-objective optimization (MOO) of rather simple and fast neural networks to search for the best network architectures in terms of the trade-off between RUL prediction error and the number of trainable parameters, the latter being correlated with …
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Parallelization of hybrid multi-objective evolutionary algorithm on multi-core architectures
Many real world optimization problems involve multiple conflicting objectives, constraints and parameters. Multi-objective optimization (MOO) techniques are used to solve these problems. The goal of MOO is to find a set of optimal solutions, or the Pareto optimal front. Multi-objective evolutionary …
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Trust-Based Service Management for Service-Oriented Mobile Ad Hoc Networks and Its Application to Service Composition and Task Assignment with Multi-Objective Optimization Goals
… a node-to-task assignment MANET application with multi-objective optimization (MOO) requirements. For either application, we propose a trust-based algorithm to effectively filter out malicious nodes exhibiting various attack behaviors by penalizing them with trust loss, which ultimately leads to …
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Noise-Enhanced and Human Visual System-Driven Image Processing: Algorithms and Performance Limits
… quality evaluation metrics and the constrained multi-objective optimization (MOO) technique, which aims at refining the existing suboptimal image enhancement methods. Another is based on the selective enhancement framework, under which we develop several image enhancement algorithms. The two …
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Improving the dependability of safety critical wireless sensor network scheduling using artificial intelligence
… properties of safety critical WSNs as a Multi-Objective Optimisation (MOO) problem. The research methodology encompasses six key principles. Firstly, the Randomised Coverage-based Scheduling (RCS) algorithm is replicated, validated, and verified using a MATLAB simulation environment, …
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Conceptual Design of Wind Farms Through Novel Multi-Objective Swarm Optimization
… socio-economic, production, and environmental objectives of a wind energy project. To develop wind farms that are profitable, reliable, and meet community acceptance, it is critical to accomplish balance between these objectives, and therefore a clean understanding of how different design and …
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Parametric Optimal Design Of Uncertain Dynamical Systems
… which, so far, have made a robust design optimization methodology prohibitive. Some existing algorithms address uncertainty in sensors and actuators during an optimal design; however, a comprehensive design framework that can treat all kinds of uncertainty with diverse distribution …