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198 articles for “Novel algorithm”
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Simulation and Performance based Comparison of GA-Fuzzy-ANN based Shunt Active Power Filter for Power Quality Improvement in High Frequency Aircraft System
Abstract: A novel improved artificial neural network control primarily based craft shunt filter has been projected during this paper. The shunt active power filter model has been improved using Genetic algorithmic program and fuzzy logic. Genetic algorithmic program has been accustomed realize the optimum value of filter inductor; whereas fuzzy logic controller has been utilized in voltage control loop of the filter. The advance within the control scheme using artificial neural …
Published in Journal of Aerospace Engineering & Technology · Vol. 3, Issue 3, 2013 · pp. 62–70 Read article
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Artificial Intelligence in Microbiological Research: Methods, Applications and Implications
Abstract: Artificial Intelligence (AI) is revolutionising microbiological research by enabling the rapid analysis of complex biological data and improving the accuracy, efficiency, and reliability of scientific investigations. Recent advances in machine learning, deep learning, and bioinformatics have transformed AI into a powerful tool for studying microorganisms, their genetic composition, evolutionary patterns, and interactions with hosts and the environment. AI-driven computational models can process large and complex datasets far more efficiently than …
Published in Research and Reviews: A Journal of Microbiology and Virology · Vol. 16, Issue 2, 2026 · pp. 22–36 Read article
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Wear and Tribological Characteristics of Novel Metal Matrix Composites
Abstract: The development of advanced metal matrix composites (MMCs) with enhanced tribological performance has become increasingly important due to the premature failure of critical engineering components operating under severe wear conditions in automotive, aerospace, marine, defense, and power generation systems. Conventional composites such as Copper–Alumina and Aluminium–Silicon Carbide have demonstrated improved mechanical and wear characteristics; however, their widespread application is often limited by issues including particle agglomeration, non-uniform reinforcement distribution, porosity …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 1326–1346 Read article
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Deep Reinforcement Learning-Based Intelligent Energy Management Strategy for Battery–Supercapacitor Hybrid Energy Storage Systems in Electric Vehicles
Abstract: As the number of EVs increases, smart solutions for energy management are needed that will optimize energy use, prolong battery life and boost vehicle performance. The application of conventional rule based and optimization-based Energy Management Strategies (EMS) for Battery–Supercapacitor Hybrid Energy Storage Systems (HESS) often leads to sub-optimal power management, supercapacitor mismatch and battery degradation when subjected to varying driving conditions. This study aims to design an intelligent energy management …
Published in International Journal of Advanced Control and System Engineering · Vol. 4, Issue 2, 2026 Read article
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Malicious Network Traffic Detection Using Hybrid Feature Selection with Ensemble Neural Network
Abstract: The detection of malicious network traffic is a critical aspect of cybersecurity, aiming to protect sensitive data and maintain the integrity of network systems. This study introduces a novel approach that combines hybrid feature selection with ensemble neural networks to enhance the accuracy and efficiency of malicious network traffic detection. The dataset used in this study was obtained from Kaggle and offers a wide-ranging and varied collection of network traffic …
Published in Nano Trends – A Journal of Nano Technology & Its Applications · Vol. 27, Issue 3, 2025 Read article
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A Novel Strategy for Weight Initialization in Sigmoidal Feed-forward Artificial Neural Networks
Abstract: In this paper, a novel method of weight initialization is proposed. The proposed method of weight initialization distributes the initial weights and thresholds in such a manner that they lie in different regions of the activation function used at the hidden layer. The proposed method is compared with six other popular weight initialization methods on ten function approximation problems using the RPROP (Resilient Back-propagation) and Levenberg-Marquardt algorithms for training. Two …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 5, Issue 1, 2018 · pp. 62–75 Read article
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Artificial Neural Network Implementation in FPGA using Multiplexer-based Weight Updating for Efficient Resource Utilization
Abstract: This paper presents a novel scheme for field-programmable gate array (FPGA) implementation of an artificial neural network (ANN). The proposed implementation is aimed at reducing resource requirement, without compromising on the speed so that a complex ANN architecture could be realized on a single chip at a lower cost. The weight updating process in different layers of the ANN has been carried using a simple MUX-based architecture. Backpropagation algorithm which …
Published in Journal of Semiconductor Devices and Circuits · Vol. 2, Issue 1, 2015 · pp. 1–5 Read article
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Novel Laplace-domain Approach to the Electromagnetic Transients in Compensated High Voltage Power Lines
Abstract: This paper addresses the simulation of the electromagnetic transients developed in high voltage power lines, which are initiated by lightning discharges. The analysis can handle both individual and simultaneous series inductive and shunt capacitive compensation types. The sizes and locations of the compensating elements are included in the analysis. The derived Laplace s-domain mathematical model applies the concept of the ABCD transmission constants representing equivalent two-port networks. Applying the relations …
Published in International Journal of Electrical Machine Analysis and Design · Vol. 2, Issue 1, 2024 · pp. 15–21 Read article
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Molecular Docking, QSAR Modeling, and ADMET Evaluation of Novel Pyrazolo-Pyrimidine Derivatives as Potential CDK-2 Inhibitors for Cancer Therapy
Abstract: Cyclin-dependent kinase-2 (CDK-2) is an essential regulator in cell cycle progression and is an important therapeutic target in cancer drug development. In the present study, an integrated computational approach involving molecular docking studies, QSAR modeling, ADMET prediction, and artificial intelligence-based analysis was used to identify pyrazolo-pyrimidine derivatives as potential CDK-2 inhibitors. Based on the molecular docking results, it was found that selected compounds exhibited high binding affinity towards the ATP …
Published in Research and Reviews: A Journal of Pharmacology · Vol. 16, Issue 2, 2026 Read article
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A Study on AI-Enhanced Environmental Toxicology: Sensor-Driven Predictive Framework
Abstract: Traditional environmental toxicology relies heavily on labor-intensive, often retrospective, sampling and analysis, limiting our understanding of dynamic pollutant behaviors and their real-time impact on ecosystems and human health. This study presents a novel, integrated framework leveraging advanced sensor networks and artificial intelligence (AI) to revolutionize the monitoring, assessment, and predictive modeling of environmental contaminants. We deployed a sophisticated array of multi-parameter sensors (e.g., electrochemical, optical, biosensors for heavy metals, organic …
Published in Research and Reviews: A Journal of Toxicology · Vol. 15, Issue 3, 2025 Read article
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ATC Calculation in OPF Environment Using Hybrid Grey Wolf Optimizer and Particle Swarm Optimization
Abstract: Evolution of hybrid optimization provides new research direction in the real world problem solving by using more than one optimization techniques for obtaining speedy convergence and/or global optimal solution or solution near the global optimal. In this paper, a novel hybrid particle swarm optimization (PSO) and grey wolf optimizer (GWO) technique is used to calculate the available transfer capability in an optimal power flow environment. The proposed method has been …
Published in Trends in Electrical Engineering · Vol. 6, Issue 1, 2016 · pp. 84–93 Read article
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Intelligent Document Scanner
Abstract: AbstractThere is an irresistible trend in the present world for scanning the paper documents and convert it into a digitalized format. Most of these scanning treat the whole document as an entire image. In this scenario, we propose a novel “Intelligent Document Scanner” which automatically segment and classify the contents of the image document including texts, tables and images and store it as a PDF document with three sections that …
Published in Journal of Computer Technology & Applications · Vol. 7, Issue 2, 2016 · pp. 47–57 Read article
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Modeling the Novel Coronavirus Disease (COVID-19) as Hidden Markov Chains
Abstract: The Hidden Markov Model has over the years been an appropriate method for modeling diseases such as HIV AIDS, heart failure, and so on. With the ongoing pandemic affecting Nigeria by being responsible for 2,745 death cases out of 207,616 confirmed cases as of October 10, 2021, the need to study an important parameter of COVID-19, the case fatality rate by building a model and estimating the case fatality rate …
Published in Research & Reviews : Journal of Statistics · Vol. 11, Issue 4, 2022 Read article
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AI-Assisted Optimization of Supersonic Airfoil Shapes Using CFD Coupling
Abstract: This paper presents a novel framework for optimizing supersonic airfoil geometries through integrated artificial intelligence and computational fluid dynamics coupling. Traditional gradient-based optimization methods for high-speed aerodynamic shapes suffer from computational expense and convergence difficulties in non-convex design spaces. The proposed methodology employs a deep neural network surrogate model trained on high-fidelity Reynolds-Averaged Navier-Stokes solutions to approximate aerodynamic performance metrics across the design space. A hybrid particle swarm-genetic algorithm searches …
Published in Journal of Aerospace Engineering & Technology · Vol. 16, Issue 1, 2026 · pp. 8–17 Read article
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A novel similarity measure for interval value picture fuzzy Environment and extended TOPSIS
Abstract: Correct decision-making is the most arduous task in our daily life. The decisions are hard to make in the multi-criteria decision-making (MCDM) problems due to ambiguous and unexpected information. In order to cope with such uncertainties in the data, a new decision-making approach has been developed using a newly defined similarity measure under the framework of interval-valued picture fuzzy set (IVPFS), as an extension of picture fuzzy sets (PFS). In …
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 11, Issue 1, 2024 · pp. 1–10 Read article
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Automated Math Solver Assist with LLM RAG
Abstract: The challenges of solving complex mathematical problems often hinder efficiency in various scientific and engineering domains. This project proposes an innovative solution to these challenges by integrating automated math solvers with large language model (LLM) retrieval-augmented generation (RAG). The proposed system aims to streamline mathematical problem-solving processes, offering a robust and precise tool for real-time recognition, classification, and solution generation. This work provides a novel method of automating the solution …
Published in Current Trends in Signal Processing · Vol. 14, Issue 2, 2024 · pp. 25–30 Read article
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Comparative Analysis and Future Research Directions in AI in Healthcare: Medical Imaging and Diagnostics
Abstract: Artificial intelligence (AI) is reshaping healthcare, particularly in the areas of medical imaging and diagnostic practice. By using advanced techniques like machine learning and deep learning, AI systems help improve the accuracy, speed, and effectiveness of identifying diseases and analyzing medical images. This paper provides a comprehensive overview of the application of artificial intelligence in medical imaging and highlights its growing importance in clinical diagnostics. It discusses how AI-based systems …
Published in International Journal of Biomedical Innovations and Engineering · Vol. 4, Issue 1, 2026 · pp. 8–13 Read article
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A Review of Constrained Association Rule Mining
Abstract: Market basket analysis is a topic of concern when Apriori was developed. By the time, the algorithms are evolving and focusing on reducing complexity, number of database scans, using certain checking to generate only useful rules. For generating rules, firstly by support value, algorithms can extract frequent itemsets. After specifying confidence certain rules are generated. Because of generating buying pattern, a large number of areas are using association rule as …
Published in Journal of Web Engineering & Technology · Vol. 2, Issue 2, 2015 · pp. 18–22 Read article
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Analysis of Machine Learning in Metal Processing: A Novel Prospect
Abstract: Metal is processed by a wide range of procedures, from forming and casting to machining and riveting. Metal processing is a crucial part of modern manufacturing. The application of machine learning (ML) is driving a significant change in the sector, which has historically depended on empirical knowledge and trial-and-error techniques. Increased production, improved product quality, and resource optimization are expected outcomes of this action. This study aims to explore the …
Published in Journal of Materials & Metallurgical Engineering · Vol. 16, Issue 1, 2026 · pp. 41–51 Read article
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Emerging Paradigms in Parallel Computing: Trends and Innovations
Abstract: Parallel computing is at an inflection point with revolutionary new paradigms and technologies. The goal of this paper is to survey the recent trend in parallel computing from architecture, programming model and applications. Mahajan cites a litany of architectural developments such as heterogeneous computing systems with integrated graphics processing unit/central processing unit ; the emerging promise from quantum and neuromorphic architectures (please see later); advances in packing transistors using novel …
Published in Recent Trends in Parallel Computing · Vol. 12, Issue 1, 2025 · pp. 39–43 Read article