Results 71 to 80 of about 55,623 (279)

Tomtit‐Raven Evolutionary Selector‐Reinforced Attention‐Driven: A High‐Performance and Computationally Efficient Cyber Threat Detection Framework for Smart Grids

open access: yesEnergy Science &Engineering, EarlyView.
Overview of the proposed work. ABSTRACT Identifying cyber threats maintains the security and operational stability of smart grid systems because they experience escalating attacks that endanger both operating data reliability and system stability and electricity grid performance.
Priya R. Karpaga   +3 more
wiley   +1 more source

Implementing Metaheuristic Optimization Algorithms with JECoLi [PDF]

open access: yes2009 Ninth International Conference on Intelligent Systems Design and Applications, 2009
This work proposes JECoLi - a novel Java-based library for the implementation of metaheuristic optimization algorithms with a focus on Genetic and Evolutionary Computation based methods. The library was developed based on the principles of flexibility, usability, adaptability, modularity, extensibility, transparency, scalability, robustness and ...
Evangelista, Pedro   +2 more
openaire   +2 more sources

Feasibility Study and Optimal Placement of Solar Power Plants Using Binary Genetic Algorithm

open access: yesEnergy Science &Engineering, EarlyView.
This study introduces an integrated optimization framework using a binary genetic algorithm (BGA) for optimal siting and sizing of two solar plants (865 and 739 kWp) in Karaj, Iran. The BGA outperformed conventional methods, achieving a 24.3% reduction in power losses and enhanced voltage stability.
Mehrab Shahbazi, Reza Eslami
wiley   +1 more source

Chemical-Reaction-Inspired Metaheuristic for Optimization [PDF]

open access: yesIEEE Transactions on Evolutionary Computation, 2010
We encounter optimization problems in our daily lives and in various research domains. Some of them are so hard that we can, at best, approximate the best solutions with (meta-) heuristic methods. However, the huge number of optimization problems and the small number of generally acknowledged methods mean that more metaheuristics are needed to fill the
Lam, AYS, Li, VOK
openaire   +3 more sources

Probabilistic Multi‐Objective Energy Management System Model for an Energy Hub With PtG Technology for Cost Reduction and System Flexibility Improvement

open access: yesEnergy Science &Engineering, EarlyView.
Overview of the under‐study hub energy model showing the energy conversion and distribution among integrated sources and loads. ABSTRACT In this paper, a probabilistic bi‐objective energy management system (EMS) model is proposed for an energy hub (EH) equipped with renewable energy sources such as photovoltaic and wind turbine connected to the main ...
Mohammad Khoshabi   +3 more
wiley   +1 more source

Machine Learning and Artificial Intelligence Techniques for Intelligent Control and Forecasting in Energy Storage‐Based Power Systems

open access: yesEnergy Science &Engineering, EarlyView.
A new energy paradigm assisted by AI. ABSTRACT The tremendous penetration of renewable energy sources and the integration of power electronics components increase the complexity of the operation and power system control. The advancements in Artificial Intelligence and machine learning have demonstrated proficiency in processing tasks requiring ...
Balasundaram Bharaneedharan   +4 more
wiley   +1 more source

A study on gender detection using multiple classifiers on voice data

open access: yesAlexandria Engineering Journal
Researchers have frequently used metaheuristic algorithms for various problems due to their success. In data mining studies, feature selection (FS) is an essential preprocessing step for large-scale problems.
Gülnur Yildizdan, Emine Baş
doaj   +1 more source

ACO for continuous function optimization: a performance analysis [PDF]

open access: yes, 2014
The performance of the meta-heuristic algorithms often depends on their parameter settings. Appropriate tuning of the underlying parameters can drastically improve the performance of a meta-heuristic. The Ant Colony Optimization (ACO), a population based
Abraham, Ajith   +2 more
core  

A Fuzzy Framework for Realized Volatility Prediction: Empirical Evidence From Equity Markets

open access: yesJournal of Forecasting, EarlyView.
ABSTRACT This study introduces a realized volatility fuzzy time series (RV‐FTS) model that applies a fuzzy c‐means clustering algorithm to estimate time‐varying c$$ c $$ latent volatility states and their corresponding membership degrees. These memberships are used to construct a fuzzified volatility estimate as a weighted average of cluster centroids.
Shafqat Iqbal, Štefan Lyócsa
wiley   +1 more source

Metaheuristic Optimization for Sustainable Unrelated Parallel Machine Scheduling: A Concise Overview With a Proof-of-Concept Study

open access: yesIEEE Access
Sustainable development has emerged as a global priority, and industries are increasingly striving to align their operations with sustainable practices.
Absalom El-Shamir Ezugwu
doaj   +1 more source

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