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543 articles for “predictive algorithm”
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A Review of Machine and Deep Learning Techniques for Cyber Security
Abstract: Nowadays in the digital landscape, cyber threats and attacks are increasing in an exponential manner, posing server risks to organizations and critical infrastructures. Data breaches often result from sophisticated threat models that exploit vulnerabilities in networks, systems and user behaviors. Cyber solutions are increasingly incorporating machine learning and deep learning to prevent and mitigate these security issues. These technologies have the potential to detect anomalies, classify threats and predict potential …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 3, 2025 · pp. 01–07 Read article
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Bank Loan Prediction by using Logistic Regression
Abstract: In the modern era of science and technology, the banking sector is also growing very fast and a lot of people are applying for bank loans. But the bank has limited assets and can be granted to limited number of people only, so the bank must ensure that the person whom the loan is granted is eligible enough to pay it back. So, in this study, we will try to …
Published in E-Commerce for Future & Trends · Vol. 8, Issue 2, 2021 · pp. 17–21 Read article
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Data to Diagnosis: A Systematic Review of AI/ML in Healthcare
Abstract: Artificial Intelligence (AI) and Machine Learning (ML) are fast revolutionizing the diagnosis of healthcare by augmenting accuracy, speed, and efficiency. AI/ML technologies facilitate earlier and more accurate disease identification with advanced algorithms for image processing, predictive modelling, and pattern recognition, frequently outperforming conventional diagnostic techniques. This review delves into the key contribution of AI/ML in contemporary healthcare, such as its use in clinical data analysis, imaging reports, and patient histories …
Published in International Journal of Biomedical Innovations and Engineering · Vol. 3, Issue 2, 2025 Read article
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A Comprehensive Analysis of Classification Methods for Churn Prediction in Financial Services
Abstract: Persistent issues that affect long-term revenue in the banking sector include excessive client attrition. Customary churn models depend on measures related to customer satisfaction, which often result in low predictive accuracy due to their subjective nature. This study proposes an effective early warning model to address customer churn in financial services. Data is preprocessed through cleaning, one-hot encoding, Z-score normalization, and Min-max scaling. To handle class imbalance, the SMOTE algorithm …
Published in Journal of Advanced Database Management & Systems · Vol. 12, Issue 2, 2025 · pp. 47–61 Read article
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FRUDON: A Fruit Donation Platform with Convolutional Neural Network Based Fruit Shelf-life Prediction for Mitigating Starvation
Abstract: According to the United Nations Global Hunger Index, India's hunger situation is portrayed as alarming, as it ranks 101st out of 116 nations. The government predicts that 69% of children under the age of 5 years would die from malnutrition and hunger by the end of 2023, as starvation deaths have grown widespread in the nation. To tackle this concern, the mitigation of food wastage has been recognized as a …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 10, Issue 2, 2023 · pp. 27–34 Read article
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Association Rule Mining for Predicting Heart Disease: Challenges and Opportunities
Abstract: The exponential growth of digital healthcare data has spurred innovative applications of data mining techniques in medical research and practice. Among these, association rule mining stands out for its ability to uncover meaningful correlations within diverse datasets, such as electronic health records, imaging data, and genetic information. This paper reviews the application of association rule mining in predicting heart diseases, emphasizing its potential to enhance early detection, risk stratification, and …
Published in Journal of Advanced Database Management & Systems · Vol. 11, Issue 3, 2024 · pp. 29–34 Read article
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Approximation-Aware Computation for Graceful QoS Degradation in Modern Multiprocessor Operating Systems
Abstract: Modern multiprocessor operating systems face unprecedented challenges in maintaining Quality of Service (QoS) guarantees under dynamic workload conditions and resource constraints. Traditional approaches to resource management often result in abrupt service degradation or complete task failure when system resources become scarce. This study presents a comprehensive framework for approximation-aware computation that enables graceful QoS degradation in multiprocessor environments. We explore the integration of approximate computing paradigms with operating system schedulers, …
Published in Journal of Operating Systems Development & Trends · Vol. 12, Issue 3, 2025 · pp. 08–15 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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Explainable Artificial Intelligence in Personalized Medicine: Emerging Clinical Perspectives
Abstract: The convergence of artificial intelligence (AI) and precision medicine has transformed contemporary healthcare by enabling data-driven clinical decision-making, individualized therapeutic interventions, and predictive diagnostics. However, despite remarkable advances in machine learning (ML) and deep learning (DL), the widespread adoption of AI in healthcare remains constrained by the “black-box” nature of many computational systems. Clinicians, regulatory agencies, and patients increasingly demand transparency, interpretability, and trustworthiness in AI-guided medical recommendations. Explainable Artificial …
Published in Emerging Trends in Personalized Medicines · Vol. 3, Issue 2, 2026 · pp. 13–29 Read article
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Smart Air Filtration Systems for Cities: A Technological Approach to Reducing Urban Pollution
Abstract: Urban air pollution is considered one of the main ecologically critical issues of the 21st century since it threatens citizens' health through respiratory diseases, pathologies of the cardiovascular system, and even premature death. Regarding an extremely high level of pollution in large cities, it becomes necessary to realize technological solutions which could avoid the negative impact of this phenomenon. Smart air filtration systems have emerged as promising solutions for urban …
Published in International Journal of Environmental Noise and Pollution Control · Vol. 2, Issue 2, 2024 · pp. 27–42 Read article
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Analysis of The Performance of A PV/PCM System in Variable Solar Radiation Conditions
Abstract: This paper studies the performance of a PV/PCM system operating at variable solar radiation conditions. The system has been tested for six different solar radiation levels, from 250 W/m2 to 950 W/m2 determining the steady-state temperature for every case. An algorithm has been developed to predict the steady-state temperature. This prediction has produced values within 97% accuracy of experimental data. A reduction of temperature up to 18.9ºC has been achieved. …
Published in Journal of Alternate Energy Sources & Technologies · Vol. 12, Issue 1, 2021 · pp. 1–20 Read article
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An Analysis on Feature Selection Method using Real Coded Genetic Algorithm (RCGA)
Abstract: The work presented in this thesis mainly focuses on the solving protein structure prediction (PSP) problem from machine learning models. The prediction of distance-to-native of protein structure is carried out using regression machine learning models with six physicochemical properties. The objective is to predict the distance to the native like structure in the absence of its true native state and report how far a structure is from its true native. …
Published in Journal of Software Engineering Tools & Technology Trends · Vol. 5, Issue 1, 2018 · pp. 23–30 Read article
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Enhancing Healthcare Record Modeling Through Graph Convolutional Networks: Overcoming Challenges and Advancing Data Management and Analysis
Abstract: Modeling healthcare records data as a graph database presents various challenges due to the complex nature of healthcare information and its interconnectedness. In this research endeavor, our primary objective is to pinpoint the major obstacles within this field and present potential remedies to tackle them effectively. By leveraging machine learning techniques, we aim to enhance the efficiency and accuracy of healthcare record modeling, facilitating better data management and analysis. One …
Published in Journal of Software Engineering Tools & Technology Trends · Vol. 10, Issue 2, 2023 · pp. 39–50 Read article
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High-Definition Electroencephalography: A New Horizon in Neurological Pathology Research
Abstract: The advent of high-density electroencephalography (HD-EEG) has catalyzed a paradigm shift in the exploration of neurological pathologies. This editorial underscore its transformative potential in elucidating brain dynamics and refining diagnostic approaches for a spectrum of conditions, spanning from epilepsy and dementia to cognitive impairments in preterm infants. Our objective is to optimize the utility of HD-EEG by emphasizing the imperative for methodological homogenization and fostering collaborative endeavors. The remarkable spatial …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 14, Issue 2, 2024 · pp. 15–21 Read article
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Automation in Waste Management: How AI and Robotics Transforming Waste Sorting and Recycling
Abstract: Waste management is a big issue in the modern world, and it gets worse as urbanisation and industry increase. Hazards to the environment and human health result from traditional waste management practices' inability to effectively classify, recycle, and dispose of garbage. Robotics and artificial intelligence (AI) provide creative ways to improve trash processing, sorting, and collection. This article examines the application of robotics and artificial intelligence (AI) to waste management, …
Published in International Journal of Advanced Control and System Engineering · Vol. 3, Issue 1, 2025 · pp. 1–7 Read article
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Survey of Advanced Control Techniques for Active Power Filters in Grid Integration
Abstract: Active power filters (APFs) can increase power quality, dependability, and stability on power utilities by compensating for harmonic and reactive current components in power supplies. The performance and stability of active power filters are greatly enhanced by the control strategies used with them. When these two crucial elements start to compete, it is impossible to achieve both unity power factor (UPF) and flawless correction of current harmonics. A systematic review …
Published in Current Trends in Signal Processing · Vol. 13, Issue 3, 2023 · pp. 24–34 Read article
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Machine Learning Techniques Utilised for Autism Spectrum Disorder Detection
Abstract: A neurological developmental illness called autism spectrum disorder impacts a person’s ability to connect, communicate, and learn. Autism spectrum disorder influences individuals in distinct ways, as do the severity and its manifestations. Often, this illness is diagnosed in individuals between the ages of 1 and 5 years, and the symptoms include unique behaviours, interests, and potential social difficulties. In order tTo lessen the rise in instances of autism, it must …
Published in Journal of Control & Instrumentation · Vol. 14, Issue 1, 2023 · pp. 32–37 Read article
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A Correlative Study of Machine Learning Algorithms
Abstract: Machine learning (ML) is the term used to define a systematic reading of algorithms and mathematical models of computer structure used to perform a specific task without precise programming. Learning algorithms in many programs we use every day. Nowadays, one of the reasons an online search engine like Google performs so effectively is because the learning algorithm has mastered the art of rating web sites. Additional uses for these algorithms …
Published in Journal of Software Engineering Tools & Technology Trends · Vol. 9, Issue 2, 2022 · pp. 30–35 Read article
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An Investigation of Model Predictive Control in Self-driving Vehicles
Abstract: Autonomous vehicles, which are often known as self-driving automobiles or driverless cars, are vehicles that can navigate and operate without human intervention. They require efficient controllers capable of handling complexities, with reduced computational costs, and should handle multiple inputs and outputs simultaneously. Model predictive control (MPC) possesses all these characteristics which means it can be utilized effectively for the same purpose. MPC for autonomous vehicles proposes various ways of achieving …
Published in Trends in Electrical Engineering · Vol. 14, Issue 1, 2024 · pp. 40–50 Read article
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A Review on Predicting Wear and Friction of PTFE Composites - Fillers to Machine Learning Models
Abstract: Polytetrafluoroethylene (PTFE) composites, a self-lubricating material with low friction, became an indispensable material in engineering applications where load carrying capacity and wear are crucial. The pure PTFE has poor mechanical strength and wear resistance which can be enhanced by the addition of fillers in appropriate volume fraction. The wear performance is dependent on various factors such as fillers, operating parameters, environmental conditions as well as manufacturing attributes. This makes the …
Published in Journal of Polymer & Composites · Vol. 13, Issue 4, 2025 · pp. 114–128 Read article