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26 articles for “GA–genetic algorithm”
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Nymphaea lotus (Indian Lotus) Analysis with Genetic Algorithm
Abstract: There is a significant problem with the availability of medicinal plants for the treatment of various diseases. Nymphaea lotus (Indian lotus) is one such plant, which is primarily available in the Indian subcontinent. This paper investigates the analysis of this medicinal plant with the help of a genetic algorithm. Himalayan yew, false black pepper, Indian snakeroot, and Indian lotus are four medicinal plants. These four have some unique medicinal values, …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 1, Issue 2, 2023 · pp. 18–22 Read article
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Machine Learning-Assisted Design and Optimization of Lightweight Polymer Composites for IoT-Enabled Automotive Applications
Abstract: This study aims to develop an integrated machine learning and optimization framework for the intelligent design of lightweight polymer composites suited for IoT-enabled automotive applications. The goal is to enhance material performance while satisfying multiple design constraints such as mechanical strength, thermal stability, and process compatibility. A curated dataset of polymer composite formulations was used to train a Random Forest Regression (RFR) model capable of predicting tensile strength, thermal conductivity, …
Published in Journal of Polymer & Composites · Vol. 13, Issue 5, 2025 · pp. 12–27 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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A Novel Approach for Design and Optimization of Slot Antenna for WLAN Applications
Abstract: The simulation, and analysis of a micro-strip fed slot antenna array intended for operation in the 2.4 GHz ISM (Industrial, Scientific, and Medical) band, which is widely used for wireless technologies such as Wi-Fi and Bluetooth. A slot antenna is a type of antenna where a slot (cut or gap) is made on a metal surface, and it radiates electromagnetic waves. Utilizing ANSOFT HFSS software, the antenna's performance is optimized, …
Published in Journal of Microwave Engineering and Technologies · Vol. 12, Issue 1, 2025 · pp. 1–12 Read article
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Impact of Layer Height and Infill Line Orientation On 3D Printed Components Produced Via Additive Manufacturing
Abstract: Additive Manufacturing (AM) is an extrusion-based technique used to create objects by extruding semi-molten material through a nozzle of specific dimensions. Materials like acrylonitrile butadiene styrene (ABS), polylactic acid (PLA), polycarbonate (PC), and others are commonly employed in this process to manufacture industrial components. The mechanical properties of engineering component are critical for various industrial applications. This study investigates the impact of additive manufacturing on fabrication, considering different process parameters. …
Published in Journal of Polymer & Composites · Vol. 13, Issue 3, 2025 · pp. 315–323 Read article
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Codal Validation and Optimization of Gantry Girders Under Variable Wheelbase and Impact Loads: A Review of Analytical, Numerical, and Codal Approaches
Abstract: Gantry girders serve as critical structural elements in industrial facilities such as steel plants, workshops, and heavy manufacturing units, where electric overhead traveling (EOT) cranes operate. The design of these girders is governed by stringent codal provisions to ensure safety under bending, shear, and deflection. However, discrepancies between codal predictions, analytical formulations, and finite element analysis (FEA) results, particularly under variable wheelbase and dynamic impact loads, have been widely reported. …
Published in Journal of Offshore Structure and Technology · Vol. 12, Issue 3, 2025 · pp. 23–29 Read article
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Implementation of Anticipating Rainfall Using Machine Learning
Abstract: Rainfall forecasting is crucial for many aspects of our national economy and should help prevent major seasonal droughts. Since agriculture is a beloved profession in many states, some Asian countries are economically hooked to decline. Previous precipitation info is beneficial. Farmers are cancerous in managing their crops, resulting in economic progress for the country. downfall prediction is hard for earth science scientists because of unordering time and unordered quantity of …
Published in International Journal of Satellite Remote Sensing · Vol. 1, Issue 1, 2023 · pp. 1–8 Read article
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Optimal Placement and Sizing of STATCOM for Loss Reduction and Voltage Profile Enhancement Using Genetic Algorithm
Abstract: Electric power distribution networks frequently experience significant power losses and voltage profile deterioration due to increasing load demand and inadequate reactive power compensation. This study investigates the enhancement of the Eleme distribution network in Rivers State through voltage upgrading and optimal deployment of a Static Synchronous Compensator (STATCOM). The existing network consists of a 5.56 km, 11 kV radial distribution system supplying seventeen distribution transformers with a cumulative load demand …
Published in Journal of Power Electronics and Power Systems · Vol. 16, Issue 2, 2026 Read article
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Multi-Objective Optimization of Polymer-Based Functionally Graded Composites for Lightweight Structures
Abstract: Functionally graded composites (FGCs) improve lightweight structural performance by allowing material properties to change smoothly across a component. Polymer-based FGCs (P-FGCs), in particular, are gaining prominence in aerospace, automotive, and biomedical industries due to their excellent strength-to-weight ratio, tunability, and ease of processing. However, optimizing these materials for lightweight structural applications requires addressing conflicting design objectives, such as maximizing stiffness while minimizing weight or enhancing thermal resistance while maintaining manufacturability. …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 961–973 Read article
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The Convergence of AI and Composites - A Review Anchored in Patent Trends
Abstract: The integration of artificial intelligence (AI) and machine learning (ML) techniques is revolutionizing the design, analysis, and optimization of polymer (PC/FRP), metal (MC), and ceramic matrix composites (CC). Techniques such as artificial neural networks (ANN), deep learning (DL), genetic algorithms (GA), and physics-informed machine learning (PIML) are employed to enhance property estimation, process optimization, and predictive modeling. These AI-driven frameworks enable virtual testing, application-specific material design, and real-time decision-making, while …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 182–198 Read article
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AI-Driven Multi-Objective Optimization of Conductive Polymer Composites for High-Performance Flexible Electronics
Abstract: The development of conductive polymer composites (CPCs) is critical for advancing flexible and wearable electronic technologies. However, the conventional trial-and-error approach to material formulation is time-consuming and often inefficient due to the high-dimensional nature of the design space. This study introduces a novel AI-driven framework that integrates machine learning (ML) with multi-objective optimization to accelerate the discovery of high-performance CPCs. A dataset of 1,000 experimentally reported formulations was compiled, capturing …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 734–745 Read article
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Systematic Review of Application of Nature-Inspired Algorithms for Resource Optimization in Multi-Programmed Operating Systems
Abstract: Multi-programmed operating systems are increasingly confronted with complex challenges in efficiently managing system resources, primarily due to the need to handle numerous concurrent processes with diverse and often conflicting resource demands. As these systems evolve, ensuring optimal performance across various dimensions, such as CPU scheduling, memory allocation, and load balancing, has become crucial. In this context, nature-inspired algorithms have emerged as promising solutions for enhancing resource optimization. These algorithms, which …
Published in Journal of Operating Systems Development & Trends · Vol. 12, Issue 2, 2025 · pp. 08–14 Read article
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Performance, Combustion and Emission analysis of Sunflower oil based Biodiesel using Non-Dominated Sorting Genetic Algorithm-II
Abstract: Biodiesel is used as alternate fuel of I. C. Engines for so many years. It is obtained from various edible and non-edible oils including waste cooking oils through trans-esterification process in the presence of catalyst. The suitable amount of biodiesel mix with commercial diesel can be used to run the compression ignition engines. The optimum combination of engine input parameters is the challenging task as required by the design engineer …
Published in International Journal of Energy and Thermal Applications · Vol. 1, Issue 1, 2023 · pp. 1–6 Read article
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A Memory-Based Genetic Algorithm for Optimization of Power Generation in a Microgrid
Abstract: Due to advancement in power electronics field, it is becoming more feasible to integrate renewable energy into power grid. Renewable energy sources are prompting more and more small investors to invest in generation and distribution of renewable energy at microgrid level. The increased competition requires energy producers to offer energy at minimum possible cost to gain the confidence of consumers, which needs efficient methods to schedule energy generation among the …
Published in Journal of Semiconductor Devices and Circuits · Vol. 12, Issue 3, 2025 · pp. 29–38 Read article
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Enhancing Production Line Efficiency: Simulating and Optimizing Single and Parallel Line Processes
Abstract: During a time of fast-paced industrial growth, increasing production line effectiveness is a core issue for manufacturers looking to maximize output, reduce waste, and stay competitive. This study explores the use of simulation-based optimization methods to enhance single and parallel production line designs. Stepping beyond traditional trial-and-error methods, the research utilizes Siemens Tecnomatix Plant Simulation to simulate actual manufacturing scenarios, considering intricacies like buffer capacities, machine sequencing, and event-driven scheduling. …
Published in Journal of Production Research & Management · Vol. 15, Issue 1, 2025 · pp. 22–32 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-Driven Pharmacogenomics and Precision Medicine: Future of Personalized Therapy
Abstract: Pharmacogenomics and artificial intelligence (AI) are emerging as important drivers of precision medicine, enabling healthcare systems to adopt individualized therapeutic approaches. Pharmacogenomics examines how genetic variations influence drug response, efficacy, metabolism, and toxicity, while AI provides advanced computational tools for analyzing complex genomic and clinical data. This review highlights the integration of AI-driven pharmacogenomics in personalized therapy and its potential to improve treatment outcomes. Machine learning, deep learning, natural language …
Published in Emerging Trends in Personalized Medicines · Vol. 3, Issue 2, 2026 · pp. 1–12 Read article
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Recent Update on Advanced Drug Delivery System
Abstract: Over the past decade, there has been a growing interest in the use of artificial intelligence (AI) technology for analysing and interpreting biological or genetic data, accelerating drug discovery, and identifying selective small-molecule modulators or rare molecules in addition to predicting their behaviour. The use of artificial neural networks (ANNs) for the rapid analysis of massive amounts of data, the development of novel hypotheses and treatment plans, the prediction of …
Published in International Journal of Advance in Molecular Engineering · Vol. 1, Issue 1, 2023 · pp. 22–30 Read article
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AI Application in the Creation of Medications for COPD
Abstract: The crippling lung condition known as chronic obstructive pulmonary disease (COPD) is typified by a continuous restriction of airflow, which results in increased respiratory dysfunction and a reduced quality of life. The rising incidence of COPD worldwide emphasizes the pressing need for innovative pharmaceutical approaches to address the illness. Even though COPD care has advanced significantly, most current medications concentrate on symptom relief rather than disease change. This gap in …
Published in Research & Reviews: A Journal of Drug Design & Discovery · Vol. 12, Issue 2, 2025 · pp. 01–05 Read article
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Progression of Health and Wellness: Artificial Intelligence (AI) and Deep Learning (DL) for Precision Medicines
Abstract: Deep learning and artificial intelligence in the field of precision medicine is revolutionizing healthcare to make personalized therapeutic approaches desirable based on the unique characteristics of the patient. AI technologies improve diagnostic accuracy by analyzing medical data, spotting patterns and anomalies that human experts may miss. AI-driven models are instrumental in precision medicine, where they can predict patient response to therapies to tailor treatment plans, enhancing outcomes and reducing adverse …
Published in Emerging Trends in Personalized Medicines · Vol. 2, Issue 2, 2025 · pp. 1–5 Read article