Pages that link to "Item:Q1011915"
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The following pages link to Design optimization of electric motors by multiobjective fuzzy genetic algorithms (Q1011915):
Displaying 15 items.
- Mixed-variable optimal design of induction motors including efficiency, noise and thermal criteria (Q535700) (← links)
- Application of non-dominated sorting genetic algorithm-II technique for optimal FACTS-based controller design (Q609769) (← links)
- Optimization shape of variable capacitance micromotor using differential evolution algorithm (Q624738) (← links)
- Optimization of total harmonic current distortion and torque pulsation reduction in high-power induction motors using genetic algorithms (Q1045551) (← links)
- A comparative study of stochastic optimization methods in electric motor design (Q2383966) (← links)
- Efficiency determination of induction motors using multi-objective evolutionary algorithms (Q2654489) (← links)
- System optimization by multiobjective genetic algorithms and analysis of the coupling between variables, constraints and objectives (Q3368682) (← links)
- A multi‐objective analysis of a special switched reluctance motor (Q3368703) (← links)
- Design optimization of three‐phase energy efficient induction motor using adaptive bacterial foraging algorithm (Q3588986) (← links)
- Optimal design of single‐phase induction motor using particle swarm optimization (Q3591243) (← links)
- Genetic algorithm‐based multi‐objective optimization of an exciter for magnetic induction tomography (Q3645102) (← links)
- Application of modified FBT algorithm in induction motor series optimal design (Q4255091) (← links)
- Development of optimizing method using quality engineering and multivariate analysis based on finite element method (Q4823782) (← links)
- Specific power as objective function in GA optimal design of permanent magnet disc motor (Q4932984) (← links)
- Multiobjective optimal design of three‐phase induction motor using simulated annealing technique (Q5707809) (← links)
