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55 articles for “Evolutionary Algorithm”
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Design of Differential Evolution Optimized PI Controller for a Temperature Process
Abstract: Differential evolution is a new stochastic population-based optimization algorithm. It is an accurate, fast and robust optimization method. In this paper, a PI controller is used and differential evolution optimization technique is used to optimize the controller parameters. The robust controller parameters are obtained by solving the optimization problem, which consists of objective functions and constraints, using differential evolution method. Here differential evolution is implemented in tuning of a PI …
Published in Journal of Control & Instrumentation · Vol. 3, Issue 1-3, 2012 · pp. 17–26 Read article
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The Role of AI in Modern Circuit Design and Simulation
Abstract: The integration of artificial intelligence (AI) in circuit design and simulation is revolutionizing the electronics industry by enabling faster, more efficient, and innovative design processes. This article explores the transformative role of AI in automating tasks traditionally reliant on manual expertise, such as schematic generation, component optimization, and fault detection. It highlights how machine learning algorithms and generative AI tools are improving design accuracy, reducing time-to-market, and enabling cost-effective prototyping. …
Published in Journal of Semiconductor Devices and Circuits · Vol. 12, Issue 1, 2025 · pp. 9–14 Read article
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Speed Control of PMSM using Optimization Methods
Abstract: AbstractThis paper represents a modelling and optimized design of speed control for a permanent magnet synchronous motor (PMSM). The PI controller of inner current loop is optimized using evolutionary algorithm like Particle Swarm Optimization (PSO) method. To illustrate effect of proposed method, the performance of evaluationary algorithm is compared with traditional optimization method i.e., Ziegler-Nichols method. The main objective of the proposed work are, develop mathematical modelling of PMSM motor …
Published in Journal of Microcontroller Engineering and Applications · Vol. 6, Issue 2, 2019 · pp. 8–16 Read article
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Revolutionizing Urban Traffic Management: An AI and Multi-Agent System Approach Leveraging IoT Technology
Abstract: Our study addresses the challenging issue of traffic congestion in modern urban areas and the limitations of traditional solutions like road expansion and network indicators. To effectively tackle traffic congestion, the study explores various strategies that analyze traffic elements, falling into the Macroscopic and Microscopic Models. However, conventional traffic modeling faces significant challenges in dealing with complex traffic systems.Artificial Intelligence (AI) techniques, including fuzzy logic, evolutionary algorithms, neural networks, and …
Published in Trends in Transport Engineering and Applications · Vol. 10, Issue 3, 2023 · pp. 1–8 Read article
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Generation Scheduling Using Quantum Inspired Evolutionary Programming
Abstract: A new novel evolutionary algorithm based on principles of quantum mechanics known as quantum inspired evolutionary programming (QIEP) has emerged as a modern optimization technique. QIEP is unique than other evolutionary programming for its qubit representation and superposition of states. QIEP has proven its applicability in different combinatorial problems successfully. It can also be applied in power system optimization problem. In this paper, we have used QIEP for generation scheduling. …
Published in Trends in Electrical Engineering · Vol. 5, Issue 1, 2015 · pp. 12–15 Read article
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An Overview, Changes, and Uses of the Novel Social Spider Optimization Algorithm
Abstract: The rising complexity of real-world problems has prompted researchers and computer scientists to look for more effective ways to solve difficulties. Generally inspired by nature, bioinspired metaheuristics based on swarm intelligence algorithms and evolutionary computation have been widely employed to solve complicated, real-world optimization problems because of their adaptability to a broad variety of factors. The social spider optimization (SSO) approach is introduced in this article as a swarm-based algorithm, …
Published in Journal of Software Engineering Tools & Technology Trends · Vol. 10, Issue 3, 2023 · pp. 61–71 Read article
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Accelerating Unsupervised Feature Learning: Parallelized Training of Denoising Autoencoders
Abstract: Unsupervised representation learning has become a cornerstone of contemporary machine learning, enabling algorithms to extract informative features from un-labelled, high-dimensional data. This work investigates the efficacy of stacked denoising autoencoders (SDAEs) trained via parallelized stochastic gradient descent (SGD) as a scalable approach to feature extraction. By strategically leveraging multi-threaded computation, our study systematically examines the trade-offs between increased parallelism, training efficiency, and the preservation of model accuracy. Experiments on the …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 12, Issue 3, 2025 · pp. 56–64 Read article
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Automating Compiler Optimization: A Machine Learning Approach
Abstract: This study reports on an ML-based approach to compiler optimization, complementing traditional optimization methods that rely strongly on hand-tuned settings. Compiler optimization plays a key role in performance-speedup and energy optimization of complex contemporary software systems. However, the traditional approach to optimizer settings involves laborious, error-prone, and scale-insensitive human-in-the-loop intervention, especially in the complex and high-demand environments in which today's computing application thrives. By integrating RL and GA, we can …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 1, 2025 · pp. 12–16 Read article
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AI-Enabled Optimization of Additively Manufactured Composite Materials for Enhanced Mechanical and Thermal Performance
Abstract: This paper discusses the optimization of multi-objective optimization of enhanced coupling of heat and mechanical properties of 3D printed polymer composite materials by artificial intelligence (AI), as a component of a multi-objective optimization framework. It aims at development of nonlinear printing parameters and material properties relationships to achieve maximum tensile strength and thermal conductivity in polymer composites produced through fused deposition modeling (FDM). Short carbon fiber reinforcement was used to …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 867–891 Read article
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Design Simulation of Improvement of Voltage Profile and Loss Minimization by Efficient Placement of Distributed Generation in Grid Connected System
Abstract: Electricity consumption is rapidly increasing, and the gap between generation and load is widening. The mismatch between demand and load causes a range of problems, including failure, low power, and, in certain cases, blackout. These issues will be solved by including Distributed Generation (DG) into the system. For maximum dependability, technological and economic benefits, and optimal size and capabilities of distributed generators, the proper distribution of power systems, kind of …
Published in Journal of Electronic Design Technology · Vol. 12, Issue 2, 2021 · pp. 1–9 Read article
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Numerical Simulation of Hybrid GSA Based Optimal Power Flow for Multi Objective Optimization Strategy
Abstract: Restricted nonlinear optimization in electric power systems engineering is a topic of Optimal Power Flow (OPF) that has been extensively investigated. It has been a long and remarkable history for the OPF, which was founded in the 1960s, of research and publication. Newcomers to OPF research face a challenging undertaking since there is so much information available and because OPF's popularity within the electric power systems community has prompted authors …
Published in Journal of Instrumentation Technology & Innovations · Vol. 11, Issue 3, 2021 · pp. 24–32 Read article
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Genetic Algorithm Based Simulation for IEEE-30 Bus System Multi-Objective Power Flow Design
Abstract: In order to control and orchestrate profitable power structures, OPF algorithms are a critical area of research. Perfect Power Flow is utilised to keep objective work to a minimum. This goal restriction might be a single goal or a set of goals. In this work, we used a perfect energy stream to reduce the cost of fuel while meeting constraints such as generator tension and electrical yields, which are used …
Published in Journal of Electronic Design Technology · Vol. 12, Issue 3, 2021 · pp. 9–15 Read article
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Numerical Simulation of Multiple Objective Power Flow Optimization in IEEE-30 Bus System Using Improved Particle Swarm Optimization
Abstract: OPF algorithms are an important research topic for the management and orchestration of profitable power structures. Perfect Power Flow is used to limit the objective work. This goal cap can be a single goal or various aim limits. In this study, we have carried out a perfect energy stream to limit the cost of fuel while fulfilling limitations, such as the tension and the electricity yields of the generator, which …
Published in Recent Trends in Electronics Communication Systems · Vol. 8, Issue 2, 2021 · pp. 23–28 Read article
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A CON: EVO Reduction Technique for Uncertain Interval Systems Using Differential Evolution Algorithm
Abstract: In this paper advantage of evolutionary technique is used in combination with a reliable conventionaltechnique to reduce the dimension of high order uncertain linear interval systems into low order intervalsystems. The proposed technique is depicted by a name CON: EVO, which stands for combination ofconventional & evolutionary technique. In evolutionary method recently proposed Differential Evolution(DE) optimization technique is used with and without powerful conventional Routh approximation techniqueto minimize the integral …
Published in Journal of Control & Instrumentation · Vol. 1, Issue 1-2-3, 2011 · pp. 1–11 Read article
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Economic Load Dispatch with PEV Using Evolutionary Techniques
Abstract: In this paper, the Economic Load Dispatch (ELD) problem is solved by using four different evolutionary techniques Social Spider Algorithm (SSA), Particle Swarm Optimization (PSO), and Teaching Learning Based Optimization (TLBO) with PEV on 20-unit thermal generation station. The most recent Self-Learning Teaching Learning Based Optimization (SL-TLBO) is introduced, including a weighting factor w for adjusting the learning range. A comprehensive study demonstrates that the unique algorithm has the potential …
Published in Journal of Thermal Engineering and Applications · Vol. 10, Issue 3, 2023 · pp. 22–33 Read article
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Integrating Genetic Algorithms with Lean Manufacturing for Enhanced Production Efficiency
Abstract: Lean manufacturing is a well-established philosophy focusing on the systematic reduction of waste and the ongoing development of value supplied to the customer. It emphasizes efficiency, quality, and adaptability through ideas such as just-in-time production, continuous improvement (Kaizen), and value stream optimization. However, the increased complexity of modern production systems, driven by global rivalry, product variety, and rapid technology innovation, has shown the limitations of classic lean tools in achieving …
Published in Journal of Production Research & Management · Vol. 15, Issue 3, 2025 · pp. 38–43 Read article
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An Improvement of Voltage Stability by Generator Bus Rescheduling
Abstract: This paper focuses on assessment and improvement of voltage stability by Georgeoschrin’s theorem using new evolutionary TLBO and PSO algorithm. In today’s environment, voltage stability maintained without sacrificing the power system parameters is really a herculean task. Generally, eigen value of reduced Jacobian matrix or Jacobian matrix of N-R base load flow analysis is well thought-out as voltage stability indices for weak bus identification. Here, the diagonal elements reduced Jacobian …
Published in Trends in Electrical Engineering · Vol. 7, Issue 2, 2017 · pp. 1–10 Read article
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Optimization of Resin 3D Printing Process Parameters for Enhanced Dimensional Accuracy and Surface Roughness Using Hybrid Algorithm
Abstract: The advent of 3D printable dental resin has paved the way for minimally invasive dentistry, which helps to retain healthy tooth structure while yet producing pleasing aesthetic outcomes. However, printing these dental resins is being researched to improve their durability and therapeutic efficacy. Frontiers in dental restoration research can aim to fabricate occlusal appliances using resins with optimized parameters for enhanced functionalities. The present study aims to analyze the dimensional …
Published in Journal of Polymer & Composites · Vol. 11, Issue 3, 2023 · pp. 26–37 Read article
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Evolutionary Particle Swarm Optimization (EPSO) based technique considering Voltage Stability Margin for Reactive Power Reserve Optimization
Abstract: Reactive power reserve and voltage stability are one of the important parameters required for proper operation of the electrical power system. Voltage stability covers a broad span of phenomena in power systems and its applications. Voltage stability is defined as ability of power system to assist fixed bearable potential at every single bus of the system under standard operating conditions and when put through to a disturbance. At any instant …
Published in Journal of Power Electronics and Power Systems · Vol. 11, Issue 2, 2021 · pp. 36–41 Read article
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Genetic Algorithm: an Optimization Tool for Real World Problems
Abstract: AbstractThe main goal of this research work is to give the lesson on genetic algorithm with the help of evaluation concept of our environment. Genetic algorithm is a type of optimization algorithm, means it is used to find the optimal solution to a given computational problem that maximizes or minimizes a function. Genetic algorithms represent a branch of the field of study called evolutionary computation, in which they imitate the …
Published in Journal of Energy, Environment & Carbon Credits · Vol. 9, Issue 3, 2019 · pp. 17–21 Read article