Metaheuristic design of feedforward neural networks: A review of two decades of research
Over the past two decades, the feedforward neural network (FNN) optimization has been a
key interest among the researchers and practitioners of multiple disciplines. The FNN …
key interest among the researchers and practitioners of multiple disciplines. The FNN …
Modern electrical machine design optimization: Techniques, trends, and best practices
Disruptive innovations in electrical machine design optimization are observed in this paper,
motivated by emerging trends. Improvements in mathematics and computer science enable …
motivated by emerging trends. Improvements in mathematics and computer science enable …
More robust and reliable optimized energy conversion facilitated through electric machines, power electronics and drives, and their control: State-of-the-art and trends
According to the special section entitledRobust design and analysis of electric machines
and drives', to be published in IEEE Transactions on Energy Conversion, the authors …
and drives', to be published in IEEE Transactions on Energy Conversion, the authors …
Optimization of high-performance concrete mix ratio design using machine learning
B Chen, L Wang, Z Feng, Y Liu, X Wu, Y Qin… - … Applications of Artificial …, 2023 - Elsevier
High-durability concrete is required in extremely cold or ocean environments, making the
design of concrete mixes highly important and complicated. In this study, a hybrid intelligent …
design of concrete mixes highly important and complicated. In this study, a hybrid intelligent …
Machine learning-based multiobjective optimization of pressure swing adsorption
The transient, cyclic nature and flexibility in process design make the optimization of
pressure swing adsorption (PSA) computationally intensive. Two hybrid approaches …
pressure swing adsorption (PSA) computationally intensive. Two hybrid approaches …
Surrogate-assisted genetic programming with simplified models for automated design of dispatching rules
Automated design of dispatching rules for production systems has been an interesting
research topic over the last several years. Machine learning, especially genetic …
research topic over the last several years. Machine learning, especially genetic …
[HTML][HTML] Constrained, mixed-integer and multi-objective optimisation of building designs by NSGA-II with fitness approximation
AEI Brownlee, JA Wright - Applied Soft Computing, 2015 - Elsevier
Reducing building energy demand is a crucial part of the global response to climate change,
and evolutionary algorithms (EAs) coupled to building performance simulation (BPS) are an …
and evolutionary algorithms (EAs) coupled to building performance simulation (BPS) are an …
Multiobjective optimization of a hollow plunger type solenoid for high speed on/off valve
S Wu, X Zhao, C Li, Z Jiao, F Qu - IEEE Transactions on …, 2017 - ieeexplore.ieee.org
This paper presents the modeling, optimization, and validation of a hollow plunger type
solenoid for high speed On/Off valve. In the preliminary design, an accurate equivalent …
solenoid for high speed On/Off valve. In the preliminary design, an accurate equivalent …
A novel approach for fuel cell parameter estimation using simple genetic algorithm
K Priya, TS Babu, K Balasubramanian… - Sustainable Energy …, 2015 - Elsevier
A new problem formulation for effective identification of fuel cell parameters is proposed. The
proposed formulation is solved by applying Genetic Algorithm optimization technique. The …
proposed formulation is solved by applying Genetic Algorithm optimization technique. The …
An efficient differential evolution algorithm for stochastic OPF based active–reactive power dispatch problem considering renewable generators
Optimal active–reactive power dispatch problems (OARPD) are non-convex and highly
nonlinear complex optimization problems. Typically, such problems are expensive in terms …
nonlinear complex optimization problems. Typically, such problems are expensive in terms …