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901 articles for “algorithmic”
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A Survey of Several Machine Learning (ML) Algorithms for Security Solution in Internet of Things (IoT) Networks
Abstract: The Internet of Things (IoT) refers to the integration of physical objects with the Internet, allowing for connectivity and monitoring. This idea has garnered immense attention from researchers and users alike, driven by the widespread accessibility of the Internet. It spans a wide range of devices, including smart versions of conventional appliances, innovative tools tailored for Internet-enabled ecosystems, and sensors that leverage connectivity to revolutionize industries such as manufacturing, healthcare, …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 1, 2025 · pp. 1–11 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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Optimizing Routing and Placement of VLSI Circuits with Differential Algorithms and Neural Networks
Abstract: The performance of modern VLSI systems is heavily influenced by power constraints, necessitating precise power estimation and effective optimization techniques. Traditional methods, such as gate-level simulations, are often slow and computationally intensive. This paper introduces DRPENN (Differential Algorithm for Routing and Placement Optimization using Neural Networks), an innovative solution that combines a Switching Activity Estimator (SAE) with a neural network-assisted differential algorithm. By leveraging toggle rates from simulations to train …
Published in Journal of VLSI Design Tools and Technology · Vol. 14, Issue 2, 2024 · pp. 14–20 Read article
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Literature Review and Discussion of Machine Learning Algorithms for Predicting Chronic Kidney Disease
Abstract: Being one of the most serious and most occurring diseases in our era, chronic kidney disease requires a fast and correct diagnosis. The usage of machine learning in medicine has now grown to such a level that it could be a means of diagnosis. The doctor can be the first one to get the ailment by using machine learning classifier algorithms. This has been the data science sector’s new horizons, …
Published in Journal of Computer Technology & Applications · Vol. 15, Issue 3, 2024 · pp. 34–39 Read article
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Trapped in the Feed: The Psychology of Social Media Addiction, Algorithms, and Fear of Missing Out (FoMO)
Abstract: Social media has now become the most crucial part of our life which has multiple advantages, such as connecting with old friends, sharing personal experiences, creating a good social circle, and accessing knowledgeable information. However, excessive use can result in social media addiction. This research paper aims to determine the psychology behind social media addiction and its factors, how the psychological behaviors can lead to social media addiction, the role …
Published in OmniScience: A Multi-disciplinary Journal · Vol. 14, Issue 3, 2024 · pp. 8–19 Read article
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Optimization of Turning Process Parameters by Genetic Algorithm Approach
Abstract: In this research, turning parameters were optimized through a genetic algorithm for the purpose to minimize surface roughness and to maximize the material removal rate. High finish quality is guaranteed through minimum surface roughness, and efficient process planning is facilitated through maximum material removal rate optimization. For predicting surface roughness and material removal rate with respect to spindle speed, feed rate, and depth of cut, the empirical models were developed …
Published in Journal of Production Research & Management · Vol. 15, Issue 1, 2025 · pp. 33–41 Read article
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Firefly Algorithm–Based Optimization of Processing Parameters for Enhanced Performance of Polymer Composite Materials
Abstract: Polymer composite materials are extensively used in aerospace, automotive, and oil & gas applications due to their high strength-to-weight ratio and design flexibility. However, achieving optimal mechanical and thermal performance strongly depends on precise control of processing parameters such as curing temperature, energy consumption, and material utilization. Conventional trial-and-error approaches often lead to excessive energy usage, non-uniform curing, and sub-optimal composite properties. To address these challenges, this paper proposes an …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 90–107 Read article
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Algorithmic Ecology: A Framework for Achieving Carbon-Neutrality in Global Data Infrastructure
Abstract: The exponential growth of digital infrastructure has positioned data centers as critical enablers of the global digital economy, yet their environmental impact has become a paramount concern. Data centers consumed approximately 205 TWh globally in 2018, representing about 1% of global power usage with a steady 6% growth trend. This review synthesizes current literature on green algorithms and sustainable data center technologies, examining the intersection of artificial intelligence, machine learning …
Published in International Journal of Sustainability · Vol. 3, Issue 1, 2026 · pp. 33–48 Read article
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Super-twisting Algorithm Based Sliding Mode Controlled Boost Converter
Abstract: This work provides analysis of boost converter with super-twisting algorithm under sliding mode operating in continuous conduction mode. The super-twisting algorithm reduces the chattering effect which is inherent in conventional sliding mode control. Generally, chattering increases heat losses, thereby decreasing the performance of the boost converter. The aforementioned control strategy minimizes the initial current peak and provides highly improved output voltage regulation irrespective of the input voltage perturbation and load …
Published in International Journal of Electro-Mechanics and Material Behaviour · Vol. 2, Issue 1, 2024 · pp. 38–48 Read article
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Alzheimer’s Disease Detection Using ML Algorithm
Abstract: A degenerative neurological state of affairs, Alzheimer's disease (AD) gradually impairs cognitive and functional capacities, especially in people over 65. Early AD detection is crucial for efficient management and treatment prep. This study delves into novel approaches for the early detection of AD using non-invasive methods. We've implemented a blend of neuroimaging data analysis and machine learning algorithms to pinpoint markers indicative of the disease during its initial phases. Our …
Published in Journal of Experimental & Applied Mechanics · Vol. 15, Issue 3, 2024 · pp. 53–57 Read article
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Improvement of Convergence Speed of Q-learning based Path Planning Algorithm
Abstract: Path planning is fundamental and important task of mobile robot. There are many attempts to adopt reinforcement learning (RL) in mobile robot path planning. RL based path planning is effective in path planning of intelligent mobile robot, especially in unknown environment because it doesn’t require environmental information and finds optimal path through trial-and-error process. Q-learning is one of RL algorithm widely used in path planning of mobile robots. The main …
Published in International Journal of Advanced Robotics and Automation Technology · Vol. 2, Issue 2, 2024 · pp. 19–28 Read article
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Algorithm for the prediction of cardiovascular disease (CVD)
Abstract: cardiovascular diseases (CVD) still claim a significant number of deaths globally and remain the number one killer with an annual death toll of nearly 17.9 million. While several medical advancements have been made, an early diagnosis is still hard to obtain, which often leads to worsening conditions and intricate treatment options. With the advancement of modern technology, Machine learning has demonstrated to be a miraculous tool which can greatly impact …
Published in Research and Reviews : A Journal of Immunology · Vol. 15, Issue 2, 2025 Read article
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Comparative Study of Machine Learning Algorithms for Detection of Breast Cancer
Abstract: Breast cancer continues to be the most commonly diagnosed cancer among women, with more than 2.3 million new cases diagnosed yearly worldwide. It is stated as the leading cause of cancer-related deaths. Therefore, this emphasizes the dire necessity for early diagnosis with a view to improving survival. Early diagnosis elevates the effectiveness of prediction and treatment. This research carries out a structured and analytical evaluation of various machine learning algorithms, …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 2, 2025 · pp. 113–129 Read article
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Advancements in Machine Learning: A Comprehensive Review of Algorithms, Applications, and Future Directions
Abstract: Gaining knowledge of Machine learning (ML)-guided format algorithms leverage predictive models to generate novel devices with optimized properties across several domains, which include drug discovery, fabric synthesis, and biomolecular engineering. Selecting an effective format set of policies consists of identifying appropriate hyperparameters, predictive models, and generative mechanisms to maximize format fulfilment. This study introduces an established method for set of policies requirements, ensuring that generated designs meet predefined fulfilment criteria, …
Published in Recent Trends in Programming languages · Vol. 12, Issue 2, 2025 · pp. 17–33 Read article
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Comparative Analysis of Supervised Learning Algorithms
Abstract: Supervised learning is a fundamental and widely used branch of machine learning in which models are trained on labeled datasets, meaning that each input is associated with a known output. Supervised learning algorithms develop predictive capability by understanding the mapping between input variables and corresponding output labels, enabling them to accurately forecast outcomes for previously unseen data. Due to this capability, supervised learning has found extensive applications across diverse domains …
Published in Journal of Computer Technology & Applications · Vol. 17, Issue 1, 2026 · pp. 25–30 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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Loan Prediction Using Random Forest Algorithm
Abstract: With the growth of the banking sector, more and more people are applying for bank loans. All of these loans are not allowed. The principal income of bank assets arises from the interest earned on the loan. Bank profit or loss depends largely on the amount of the loan, i.e., whether customers pay off the loan or fail. The main purpose of banks is to invest their assets in secure …
Published in Journal of Advanced Database Management & Systems Read article
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Algorithm Visualization Using CI/CD
Abstract: The visualization of algorithms demonstrates how algorithms work more efficiently. Essentially, it seeks to simplify and automate the visualization of the algorithm. Using algorithm visualizations, we have discussed how standard algorithms can be taught more effectively and efficiently with automation and further can be used as open source. Our aim is to present a way to deploy our project using CI/CD which will be a far more efficient platform. Therefore, …
Published in Journal of Computer Technology & Applications Read article
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Searching Substring in O(n) Time Complexity
Abstract: This research paper presents a highly efficient algorithm for substring search within a given string, achieving a remarkable time complexity of O(n). The proposed algorithm utilizes a two-pointer approach to compare the given string with the targeted substring. By employing string concatenation, the algorithm dynamically constructs a resultant substring during the matching process. Upon completion of character matching, the algorithm compares the resultant substring with the targeted substring and returns …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 1, Issue 1, 2023 · pp. 9–15 Read article
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Federated Learning: A Comprehensive Review of Models, Algorithms, and Business Applications
Abstract: In an age where data privacy is a significant concern, federated learning (FL) has become a game-changing method in machine learning. This decentralized model enables various parties to work together on training models without exchanging their raw data, effectively tackling the issues posed by data silos and privacy regulations. This article explores the current state of FL, including its underlying models and algorithms, practical applications, benefits, challenges, and future directions. …
Published in Current Trends in Information Technology · Vol. 14, Issue 3, 2024 · pp. 1–9 Read article