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Dynamic performance evaluation and machine learning-assisted optimization of a solar-driven system integrated with PCM-based thermal energy storage: A case study approach
Published 2025“…<p>This paper presents the design, modeling, and multi-objective optimization of an advanced solar energy system based on concentrated solar power technology, aimed at sustainable electricity generation in urban environments. …”
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262
A hybridization of evolution strategies with iterated greedy algorithm for no-wait flow shop scheduling problems
Published 2024“…The ES algorithm begins with a random initial solution and uses an insertion mutation to optimize the solution. …”
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263
A modified ant colony algorithm for evolutionary design of digital circuits
Published 2003“…In this paper, a multiobjective optimization of logic circuits based on a modified ant colony (ACO) algorithm is presented. …”
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264
Evolutionary algorithms for state justification in sequential automatic test pattern generation
Published 2005“…Evolutionary algorithms have been effective in solving many search and optimization problems. …”
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265
Chapter 19 - Metaheuristics for optimizing weights in neural networks
Published 2023“…To avoid these problems, the process of the gradient-based mechanism is replaced by a recent metaheuristic swarm-based method called horse herd optimization algorithm (HOA). …”
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266
Hybrid Cooperative Co-evolution for Large Scale Optimization
Published 2016“…In CC, multiple instances of the same evolutionary algorithm work in parallel, each optimizes a different subset of the problem in hand. …”
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267
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268
Metaheuristic algorithm for testing web 2.0 applications. (c2012)
Published 2012Get full text
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masterThesis -
269
A Genetic Algorithm for Improving Accuracy of Software Quality Predictive Models
Published 2010“…In this work, we present a genetic algorithm to optimize predictive models used to estimate software quality characteristics. …”
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270
An Optimization Approach For The Computation Of The Minimum Destabilizing Uncertainty Volume
Published 2020“…In this paper we propose an non-linear optimization based algorithm for the computation of the stability region for uncertain polynomials. …”
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271
Particle swarm optimization for multimachine power systemstabilizer design
Published 2001“…In this paper, a novel evolutionary algorithm based approach to optimal design of multimachine power system stabilizers (PSSs) is proposed. …”
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272
A stochastic iterative learning control algorithm with application to an induction motor
Published 2004“…A recursive optimal algorithm, based on minimizing the input error covariance matrix, is derived to generate the learning gain matrix of a P-type ILC for linear discrete-time varying systems with arbitrary relative degree. …”
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273
Stochastic P-type/D-type iterative learning control algorithms
Published 2003“…The optimal algorithm is based on minimizing the trace of the input error covariance matrix. …”
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274
On Higher-Order Iterative Learning Control Algorithm in Presence of Measurement Noise
Published 2005“…Furthermore, a suboptimal second-order ILC is proposed for a class of nonlinear systems. Based on a numerical example, it is shown that a compatible suboptimal first-order ILC yields better performance than the proposed suboptimal second-order ILC algorithm.…”
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conferenceObject -
275
Optimal Routing Protocol in Multimedia Wireless Sensor Networks
Published 2011Get full text
doctoralThesis -
276
Optimizing overheating, lighting, and heating energy performances in Canadian school for climate change adaptation: Sensitivity analysis and multi-objective optimization methodolog...
Published 2023“…This paper aims to develop long-term adaptation strategies for the existing Canadian school buildings under extreme current and future climates using a developed methodology based on global and local sensitivity analysis and Multi-Objective Optimization Genetic Algorithm. …”
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277
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A new tabu search algorithm for the long-term hydro scheduling problem
Published 2002“…The algorithm is based on using the short-term memory of the tabu search (TS) approach to solve the nonlinear optimization problem in continuous variables of the LTHSP. …”
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280
A hybrid model for the optimum integration of renewable technologies in power generation systems
Published 2011“…The main purpose of this work is to assess the unavoidable increase in the cost of electricity of a generation system by the integration of the necessary renewable energy sources for power generation (RES-E) technologies in order for the European Union Member States to achieve their national RES energy target. The optimization model developed uses a genetic algorithm (GA) technique for the calculation of both the additional cost of electricity due to the penetration of RES-E technologies as well as the required RES-E levy in the electricity bills in order to fund this RES-E penetration. …”
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