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543 articles for “predictive algorithm”
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Comparison of K-nearest Neighbor and Artificial Neural Network Classifiers for the Detection of Breast Cancer
Abstract: Breast cancer is the most common type of cancer seen in women in the present day, which is also considered a life-threatening disease. If this cancer can be detected in its early stage it can be a lifesaver for many people around the world. Machine Learning techniques have become one of the hotspots for predicting the early diagnosis of breast cancer. This research work experiments with the two most popularly …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 11, Issue 1, 2024 · pp. 78–83 Read article
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A Review on Loan Approval Prediction Based on Machine Learning Techniques
Abstract: The banking industry has also benefited greatly from technological advancements. An increasing number of individuals are submitting loan applications on a daily basis. When deciding which loan applicants to approve, the bank must take certain rules into account. The bank needs to choose the best one for approval based on certain characteristics. The process of carefully verifying every person and recommending them for loan approval is laborious and fraught with …
Published in Journal of Computer Technology & Applications · Vol. 15, Issue 2, 2024 · pp. 1–11 Read article
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A Smart Framework that Combines Data Mining and Optimization for Different Applications
Abstract: Blending predictive data mining with metaheuristic optimization has become essential for tackling tough, real-world problems across all kinds of fields. Most existing methods stick to fixed algorithms, each focused on a tiny slice of the puzzle, barely budging when new variables or unpredictability show up—especially with messy, human-generated data. So, here’s the idea: a Unified Metaheuristic and Predictive Data Mining (UMPDM) framework that finally connects adaptive search methods with powerful …
Published in Research and Reviews : Journal of Computational Biology · Vol. 15, Issue 2, 2026 · pp. 10–14 Read article
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Artificial Intelligence and Machine Learning Applications in Optimizing Air Conditioning Systems
Abstract: The growing demand for air conditioning systems, especially in the wake of climate change and increasing global temperatures, has led to a significant increase in energy consumption. This, in turn, contributes to the growing concerns of environmental sustainability and operational costs. As a result, there is a pressing need for innovative solutions to optimize the performance and energy efficiency of air conditioning (AC) systems. Artificial Intelligence (AI) and Machine Learning …
Published in Journal of Refrigeration, Air conditioning, Heating and ventilation · Vol. 12, Issue 1, 2025 · pp. 38–43 Read article
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An Analysis of Machine Learning Models for Early Cardiac Risk Stratification
Abstract: The paper shows an in-depth study of machine learning and artificial intelligence solutions to early cardiac risk stratification which has a crucial necessity because cardiovascular disease (CVD) prediction remains a significant issue that needs to be improved beyond the conventional risk score. Since CVD is the most serious disease killer in the world, claiming 17.9 million deaths every year, there is a strong need to get the most sophisticated predictive …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 13, Issue 2, 2026 Read article
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Federated Learning for Energy Management in Next Generation Smart Cities
Abstract: Federated learning has emerged as a promising approach for addressing the challenges of energy management in next-generation smart cities. This decentralized approach to machine learning allows collaborative model training among distributed data sources, while safeguarding data privacy and security. In this study, we explore the application of federated learning techniques to optimize energy consumption, enhance grid stability, and promote sustainability in smart city environments. By aggregating data from diverse sources …
Published in Journal of Communication Engineering & Systems · Vol. 14, Issue 1, 2024 · pp. 19–27 Read article
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Advanced Energy-Efficient Technologies, Role of Artificial Intelligence and IoT in Energy Conservation
Abstract: One of the key elements in the development of every nation's economy is energy. Due to their enormous investment requirements to meet their rising energy needs, developing nations place a high priority on the energy industry. Utilize energy management, auditing, and conservation for cost reduction and boost efficiency. Achieving and maintaining optimal energy procurement and use across the organization is the goal of energy management in order to reduce energy …
Published in Journal of Refrigeration, Air conditioning, Heating and ventilation · Vol. 12, Issue 3, 2025 · pp. 51–64 Read article
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AI-Driven Lightning Strike Prediction Using Polymer-Integrated Sensor Platforms for Climate-Resilient Energy Systems in India
Abstract: Lightning strikes are a major climate-related threat to India, resulting in severe human injuries as well as regular damages to the power transmission network and renewable energy infrastructure. This research aims to introduce the concept of an AI-based lightning strike prediction and mitigation system with the integration of polymers for making climate-resilient energy infrastructure. Multidata are collected based on satellite images, climate variables, as well as surface-based sensing modules, and …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 234–242 Read article
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Sentiment Analysis of E-Commerce Reviews using Machine Learning
Abstract: In e-commerce, sentiment pertains to the emotional responses, opinions, or perceptions that customers have about their online shopping experiences, including factors like product quality, service, and various processes such as ordering, shipping, and customer support. Sentiment analysis, which involves machine learning techniques, plays a crucial role in deciphering these sentiments. By using sentiment analysis, companies can obtain valuable insights from customer feedback from diverse online sources, including social media, surveys, …
Published in Journal of Operating Systems Development & Trends · Vol. 11, Issue 3, 2024 · pp. 25–37 Read article
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Intelligent Optimization of Drilling Parameters in Polymer Composites using Machine Learning and Metaheuristic Techniques
Abstract: The study tests different ways to use ML and metaheuristic algorithms to determine the best drilling parameters for polymer matrix composites. The research uses a composite matrix made from 55.25% vinyl ester, 44.0% Nickel–Phosphorous coated glass fiber and 0.75% Al₂O₃ nanowires which are tested for tensile strength (64.57 MPa), flexural strength (85.86 MPa) and impact strength (71.79 kJ/m²). By applying a Taguchi orthogonal array, it is observed that a slower …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 1795–1810 Read article
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A Survey on Multi Label Classification
Abstract: MultiLabel Classification is a kind of supervised learning where each instance can belong to set of multiple classes. The methods can be broadly classified into two groups: Problem Transformation and Algorithm Adaptation. Ten representative Multi Label models are scrutinized under common notations followed by different evaluation metrics. There exists wide range of application for multi label prediction such as text categorization, semantic image labeling, gene functionality etc. This survey paper …
Published in Recent Trends in Programming languages · Vol. 5, Issue 1, 2018 · pp. 19–23 Read article
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A Review Paper on Comparison of Algorithms for Supervised Machine Learning
Abstract: AbstractSupervised learning attempts to create calculations that help deliver general speculations, which is able to do forecasts about future occasions. The objective of supervised learning is to manufacture a model of the segregation of class names in terms of predictor components. The classifier produced accordingly is then used to allocate class marks to the testing data where the estimations of the indicator elements are known, yet the estimation of the …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 4, Issue 3, 2017 · pp. 11–16 Read article
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Blind Image Quality Assessment using NSS Approach in the DCT Domain
Abstract: We have develop an efficient model for improving image quality using IQA and NSS based on blind image Quality Assessment. This algorithm does computation for the parameters which user expect at output. The certain extracted features approach depends on a simple Bayesian inference model to dipict image quality scores. The project features are based on statistic scenes of discrete cosine transform for images. The resultant parameters of the model are …
Published in Recent Trends in Electronics Communication Systems · Vol. 8, Issue 4, 2021 · pp. 1–6 Read article
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Theoretical modelling of heat transfer in non-homogeneous porous media
Abstract: The paper is focused on the study and analysis of heat transfer in geothermal substrates made up of non-homogeneous porous media. The paper analyses the influence of porosity on the heat transfer as a result of the combination of conduction and convection mechanisms that take place in non-homogeneous porous materials. As a result of the combined effect heat transfer is not homogeneously distributed throughout the cross section of the geothermal …
Published in Journal of Geotechnical Engineering · Vol. 9, Issue 2, 2022 · pp. 44–51 Read article
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Automatic Baby Cry Detector with sleep music player (ABCD)
Abstract: In today’s world, our lives have become moredependent on technology. One problem which caught our eyesis when parents have to leave their wards (aged between 3months to 2 years) alone due to some essential tasks for a shortduration, the baby goes unmonitored. Normally, parents dothis by leaving their child asleep. In many cases, the childwakes up and starts to cry. In absence of loved ones, babiesneed immediate calmness relief. A …
Published in Journal of Mechatronics and Automation · Vol. 10, Issue 1, 2023 · pp. 21–29 Read article
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Blind Image Quality Assessment using NSS Approach in the DCT Domain
Abstract: We have develop an efficient model for improving image quality using IQA and NSS based on blind image Quality Assessment.This algorithm does computation for the parameters which user expect at output. The certain extracted features approach depends on a simple Bayesian inference model to dipict image quality scores. The project features are based on statistic scenes of discrete cosine transform for images. The resultant parameters of the model are used …
Published in Recent Trends in Electronics Communication Systems · Vol. 8, Issue 3, 2021 · pp. 1–6 Read article
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In Silico Identification of Antimalarial Drug Targets and Screening of Potential Inhibitors in Plasmodium vivax
Abstract: AbstractMalaria is an infectious disease caused by the protozoan of the genus Plasmodium. It is a major problem in third-world countries, with hundreds of millions of infections and millions of fatalities annually. Plasmodium vivax is the most frequent and widely distributed cause of recurring (Benign tertian) malaria. Due to emergence of drug-resistance, one has to explore new dimensions in order to curb the menace. We propose a two-step strategy—first step …
Published in Research and Reviews : Journal of Computational Biology · Vol. 9, Issue 1, 2020 · pp. 52–75 Read article
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Diagnostic Algorithm of Multidetector Computed Tomography (MDCT) for Healthy Lungs to Detect Variations of Morphologic Index
Abstract: Introduction: Diagnostic algorithm of Multidetector Computed Tomography (MDCT) was established to make qualitative diagnosis with four types of shadows-increased Lung Attenuation, Decreased Lung Attenuation, Linear Pattern, Nodular Pattern and the nodular pattern is also used for qualitative assessment by being further classified as round, lobulated, polygonal, tentacular, spiculated, ragged and irregular pattern. Method: To establish the new diagnostic algorithm using MDCT result indicators, we selected morphologic indices to used CAD …
Published in Research and Reviews : Journal of Surgery · Vol. 11, Issue 1, 2022 · pp. 30–33 Read article
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Automated Scene Surveillance using Frame Propagation from Massive Sequencization Fusion of Frame Imaging
Abstract: Remote sensing scene surveillance has already become significant contributions to many areas such; as environmental engineering and civil applications. However, these fields are still deprived from completely being automated. Since, decisions based on surveillance and sensing data in these fields strongly depend on the accuracy of these data but yet such data is produced by a measuring device and additionally being deprived from effective models and thus being generally prone …
Published in Journal of Multimedia Technology & Recent Advancements · Vol. 1, Issue 2, 2014 · pp. 4–7 Read article
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Seasonal Variation of Electric Vehicles Autonomy: Application to AC/DC Dual Voltage Operation
Abstract: In this work, a study to predict battery performance and autonomy for a dual type of electric engine, 480 VAC and 360 VDC, has been developed. The study has been conducted in vehicles of mass between 1000 and 3000 kg with battery capacity in the range of 40 to 100 kWh. The process has been simulated using reference values and modeled for specific driving conditions. The simulation has been developed …
Published in Journal of Mechatronics and Automation · Vol. 7, Issue 3, 2020 · pp. 1–15 Read article