Results 71 to 80 of about 41,487 (244)

POWER: Performance Optimization With Evaluated Results for HEV Battery Selection via MCDM‐TOPSIS

Energy Science &Engineering, EarlyView.
ABSTRACT The increasing transportation demands and environmental concerns in India necessitate the selection of optimal battery technologies for hybrid electric vehicles (HEVs). As the fifth‐largest car market globally, India faces rising vehicle demand, while the transportation sector remains a major contributor to air pollution.
Rinku Kumar Roy, Harpreet Kaur Channi, Sita Rani, Aman Kataria, Parveen Bajaj, George Uwadiegwu Alaneme   +5 more
wiley   +1 more source

State Transition Algorithm

, 2012
In terms of the concepts of state and state transition, a new heuristic random search algorithm named state transition algorithm is proposed. For continuous function optimization problems, four special transformation operators called rotation ...
A. H. Wright, A. K. Qin, C. Hamzacebi, C. Hamzacebi, D. D. Burgess, D. E. Goldberg, D. H. Wolpert, D. W. Stroock, F. J. Solis, F. V. Berth, G. Albeanu, G. Rudolph, H. A. Abbass, J. A. Nelder, J. C. Lagarias, J. J. Liang, J. Kennedy, J. Matyas, J. Y. Li, K. Deb, K. F. C. Yiu, P. Collet, R. C. Eberhart, R. Hooke, R. Storn, T. D. Tran, T. W. Leung, T. Zhang, X. J. Zhou, X. J. Zhou, X. S. Yang, Y. H. Shi, Y. X. Yuan, Z. Michalewicz   +33 more
core   +1 more source

Optimizing Electric Vehicle Charging Scheduling With Deep Q Networks and Long Short‐Term Memory‐Based Electricity and Battery State of Charge Prediction

Energy Science &Engineering, EarlyView.
Schematic diagram showing the proposed approach for EV charging/discharging. ABSTRACT The number of electric vehicles (EVs) on the road is rising as a result of recent advancements in EV technology, and EVs are important to the smart grid economy. Demand response schemes involving electric vehicles have the potential to dramatically reduce the cost of ...
F. Zonuntluanga, Subhasish Deb, Kshetrimayum Robert Singh, Subir Datta, Ahmet Onen, Taha Selim Ustun, Jaesung Jung   +6 more
wiley   +1 more source

Metaheuristic optimization algorithms: An overview

HCMCOU Journal of Science – Advances in Computational Structures
Metaheuristic optimization algorithms are versatile and adaptable tools that effectively solve various complex optimization problems. These algorithms are not restricted to specific types of problems or gradients. They can explore globally and handle multi-objective optimization efficiently.
Brahim Benaissa, Masakazu Kobayashi, Musaddiq Al Ali, Tawfiq Khatir, Mohamed El Amine Elaissaoui Elmeliani   +4 more
openaire   +1 more source

AI‐Driven Optimization of a Hybrid PV–Wind–BESS Microgrid for a Rural Educational Institution in Developing Countries

Energy Science &Engineering, EarlyView.
An AI‐driven CNN–LSTM forecasting framework is integrated with HOMER Pro to optimally design a grid‐connected PV–wind–BESS microgrid for a rural school in Bangladesh, achieving 91.7% renewable penetration, low energy cost (0.0397 USD/kWh), and an 81.5% reduction in CO2 emissions. ABSTRACT Hybrid renewable microgrid planning in HOMER Pro often relies on
Robiul Khan, Md. Wajed Ali, Md. Feroz Ali, Md. Shafiul Alam, Mohammad Ali, Imil Hamda Imran   +5 more
wiley   +1 more source

Multi-Parameter Optimization Using Metaheuristic Algorithms to Improve Uncrewed Aerial Vehicles’ Wireless Communications: A Performance Analysis

IEEE Access
Uncrewed aerial vehicles (UAVs) require robust communication for operational reliability. Recent research has explored artificial intelligence techniques, particularly metaheuristic algorithms, to address this challenge.
Lalan J. Mishra, Naima Kaabouch
doaj   +1 more source

Conceptual Comparison of Population Based Metaheuristics for Engineering Problems

The Scientific World Journal, 2015
Metaheuristic algorithms are well-known optimization tools which have been employed for solving a wide range of optimization problems. Several extensions of differential evolution have been adopted in solving constrained and nonconstrained multiobjective
Oluwole Adekanmbi, Paul Green
doaj   +1 more source

Optimized Parameter Extraction in Triple Diode Solar PV Models Using Kookaburra‐based Dwarf Mongoose Approach

Energy Science &Engineering, EarlyView.
ABSTRACT Improving photovoltaics (PV) system performance through simulation requires accurate PV models. The nonlinear relationship between current and voltage, coupled with incomplete manufacturer data, presents a significant challenge in parameter estimation.
Chappani Sankaran Sundar Ganesh, Chandrasekaran Kumar, Thangavel Swaminathan Sivakumaran, Sourav Barua   +3 more
wiley   +1 more source

A Comparative Study of Nature-Inspired Metaheuristic Algorithms in Search of Near-to-optimal Golomb Rulers for the FWM Crosstalk Elimination in WDM Systems

Applied Artificial Intelligence, 2019
Nowadays, nature-inspired metaheuristic algorithms are the most powerful optimizing algorithms for solving NP-complete problems. This paper proposes five recent approaches to find near-optimal Golomb ruler (OGR) sequences based on nature-inspired ...
Shonak Bansal
doaj   +1 more source

Weighted vertices optimizer (WVO): A novel metaheuristic optimization algorithm

Numerical Algebra, Control & Optimization, 2018
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
openaire   +3 more sources