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543 articles for “predictive algorithm”
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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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Sensor Less Control of PMSM using SMC and SMO
Abstract: Some particular PMSM applications do not allow for the proper mounting or use of position sensors. A number of PMSM control problems can be resolved with sensorless PMSM control. It is crucial to have a precise predicted position while avoiding the chattering issue for sensorless PMSM control. This paper establishes a prerequisite for a sliding mode observer (SMO) to enter a sliding surface and offers a sigmoid-based algorithm for position …
Published in Journal of Control & Instrumentation · Vol. 13, Issue 2, 2022 · pp. 27–35 Read article
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An Effective Convolutional Neural Network for Identifying Cancer Blood Disorder Cells Using Microscopic Images
Abstract: Blood, bone marrow, and lymphatic systems are all impacted by hematological cancer is known as a cancer blood disorder. Blood malignancies and various blood disorders pose significant health challenges across all age groups. Early disease detection is essential for effective cancer blood disorder treatment and management. If a blood cancer is not identified in time, it may be hazardous. It results in abnormal white blood cell production by the bone …
Published in Research and Reviews: Journal of Oncology and Hematology · Vol. 13, Issue 2, 2024 · pp. 29–35 Read article
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Implementation of K-Means clustering algorithm with technical indicators to identify Profitable stocks
Abstract: In the ever-changing world of stock market trading, accurately predicting price movements is key to maximizing profits. Technical analysis, which looks at past price data to predict future trends, provides valuable insights for investors. This paper delves into using machine learning methods, particularly the K-Means clustering algorithm, along with moving average data, to categorize daily trading patterns. By breaking down the market into clusters and examining the main patterns within …
Published in Current Trends in Signal Processing · Vol. 13, Issue 3, 2023 · pp. 8–14 Read article
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Analyzing and Predicting Academic Behavior from Peer Pressure Indicators Using Machine Learning
Abstract: The academic achievement of a student is determined by their capability, but also by the companions with whom they associate. Friends can have a positive impact on students' motivation for school, and at times friends are distractions leading to a lack of attention on their school assignments. This particular study focuses on the number and quality of companions students associate with and to what extent that could be used as …
Published in International Journal of Education Sciences · Vol. 3, Issue 2, 2026 · pp. 1–7 Read article
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Virtual Method to Predict Dental Disease
Abstract: The integration of technology and medicine in the healthcare domain has led to the emergence of inventive strategies to improve patient care and diagnostics. One such groundbreaking methodology is the utilization of Convolutional Neural Networks (CNNs) within the domain of deep learning, particularly for image recognition and processing tasks. In this paper, we propose a novel approach to image recognition that employs state-of-the-art deep learning algorithms to create a user-friendly …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 11, Issue 1, 2024 · pp. 8–15 Read article
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Predicting Software Reliability using Artificial Neural Networks: A Review
Abstract: AbstractSoftware reliability has become a major concern for all the software systems. Predicting software reliability has become a major challenge for both the software developers and the engineers. Before the software is dispensed to the market/customers, it is thoroughly checked for any errors and if errors are there, they are thereby removed. For the purpose of reliability estimation certain mathematical software reliability models have been proposed for estimating the reliability …
Published in Journal of Software Engineering Tools & Technology Trends · Vol. 6, Issue 2, 2019 · pp. 14–19 Read article
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Post Pandemic Cardiac Prediction: Analysing Heart Attack Mortality Rate In Vaccinated Adults
Abstract: Heart disease has emerged as a prominent contributor to global mortality rates. Discovered it early and providing timely management can significantly reduce the incidence of heart failures, death rates, and diagnostic costs associated with heart disease. In this study, we propose employing notification system to assess the risk of heart disease and explore potential associations between vaccination status and mortality rates due to heart attack among adult populations in the …
Published in Research and Reviews: A Journal of Health Professions · Vol. 14, Issue 2, 2024 · pp. 45–51 Read article
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Customer Churn Prediction in Life Insurance
Abstract: In order to forecast customer churn and keep consumers, life insurance firms frequently struggle to use their data efficiently. New opportunities have emerged for tackling this problem due to advancements in categorization models within the field of machine learning. In this study, we suggest an innovative method that uses machine learning classification models to forecast client churn and boost customer retention rates in the life insurance sector. Our proposed system …
Published in E-Commerce for Future & Trends · Vol. 10, Issue 1, 2023 · pp. 23–34 Read article
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Dynamic Performance Enhancement of Polymer Composites through Metaheuristic machinining optimization
Abstract: This work aims to provide an optimization of meta-heuristic algorithms in order to improve the dynamic behavior of composite materials utilized in various practical engineering tasks. Based on the Comprehensive literature review it has been observed that composite sandwich panels with PVC foam cores accomplished mechanical characteristics superior than those ones that were produced on PU foam core mainly in flexural, compression, and impact tests Thus the study establishes the …
Published in Journal of Polymer & Composites · Vol. 12, Issue 2, 2024 · pp. 114–129 Read article
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A New Evaluation Index for Application of Machine Learning Algorithms to Determine Trust in Skewed Social Media Data
Abstract: In this paper we study the problem of accuracy paradox which arises on the application of machine learning algorithms for inference of trust in skewed social media data. Skewness is defined as the under representation of one class over another in a binary classification problem. We achieved our purpose of identifying the accuracy paradox problem in various algorithms by identifying a new evaluation index called predictive index. The dataset used …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 5, Issue 3, 2018 · pp. 49–57 Read article
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AI-Powered ECG Prediction System for Detecting Cardiovascular Disease
Abstract: The proposed AI-powered CardioSmart Analyzer, an electrocardiogram (ECG) prediction system, presents an innovative and scientifically rigorous approach to the real-time automated analysis of ECG signals for diagnosing various heart conditions. This research focused on building a predictive model to identify cardiovascular diseases (CVD) using ECG data. A dataset comprising 2,840 12-lead ECG recordings was gathered from medical facilities in Gazipur, Bangladesh, over the period from June to August 2024. The …
Published in Research and Reviews: A Journal of Health Professions · Vol. 15, Issue 3, 2025 · pp. 51–85 Read article
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Detection of Cardiovascular Disease using AI and ML: A Review
Abstract: In the 21st century according to statistics, the risk of cardiovascular disease has become more common and the death rate caused by it is increasing way more. Around 17.9 million lives are taken by CVDs each year. There are various reasons causing it but most importantly it is caused by not identifying it, hence it becomes a very important task for the human race to identify the CVDs and deal …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 10, Issue 1, 2023 · pp. 11–21 Read article
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Optimization of Pesticide Requirement Calculations for IoT-Operated Hexacopter Delivery Systems
Abstract: The integration of Internet of Things (IoT) technology into precision agriculture has transformed pesticide application strategies, enabling resource-efficient and environmentally sustainable practices. This study presents a computational methodology for optimizing pesticide requirements in an IoT-operated hexacopter system, designed for dynamic, data-driven pesticide delivery. Leveraging a fusion of real-time telemetric data from onboard LiDAR, multispectral imaging sensors, and environmental monitoring modules, the system employs predictive analytics and edge computing to calculate …
Published in International Journal on Drones · Vol. 2, Issue 1, 2026 · pp. 08–14 Read article
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Material-Integrated Energy Management: Role of Advanced Polymers and Composites in Smart Homes
Abstract: The article discusses the possibility of improving the performance as well as the sustainability of smart-home-based energy management systems (EMS) by applying advanced polymeric and composite materials. Smart homes today are placing greater requirements on lightweight, thermally stable, high durability, and electrically conducting compounds in such important aspects of the devices as batteries, substrate layers in solar panels, thermally resistant enclosures, and high efficiency thermal insulation on intelligent appliances. Such …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 1361–1374 Read article
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Crop Disease Prediction by Machine Learning
Abstract: The classification of Crop can be classified into several methods. The data set of crop leaf illnesses, notably Bacterial Leaf Blight disease (BLB), a crop leaf disease with significant outbreaks throughout Thailand, and Brown Spot Crop disease (BSR), is classified employing image classification in this study. Additionally, image processing technology is used for identifying different types of crop leaf disease. These algorithms include the Random Forest, Decision Tree, Gradient Boost, …
Published in Trends in Machine design · Vol. 11, Issue 2, 2024 · pp. 21–25 Read article
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A Web Application for Predicting Diabetes Using Machine Learning Methods
Abstract: Diabetes is a long-term disease caused by high glucose quantity in the blood. It has the potential to result in serious health complications like heart disease, hypertension, and ocular damage. It is good to identify any health issues as early as possible to get the right medical treatment and make necessary lifestyle adjustments. One makes use of machine learning techniques to predict diabetes and develop treatment options using actual cases. …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 11, Issue 3, 2024 · pp. 92–102 Read article
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Machine Learning Approach to Predict the Performability and Emissions of Diesel Engine Fueled with Doped Biodiesel Blend
Abstract: Enhancing the performability and emission characteristics of diesel engines has been a difficult task in light of growing concerns about global warming and other negative effects, as diesel accounts for 70% of global energy demand. In this study, engine performance and exhaust emissions for various fuel blends were thoroughly evaluated using machine learning techniques to predict engine emission and performance behavior. We focused on biodiesel blend and nanoparticle additive concentration …
Published in International Journal of Mechanical Dynamics and Systems Analysis · Vol. 3, Issue 1, 2025 · pp. 1–12 Read article
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Prediction of Prostate Cancer Using Boosting Technique
Abstract: There are many diseases that are associated with humans, but some diseases might be associated with only males or only females. This paper shows and discusses the disorder that is associated mainly in men. Prostate cancer is associated with the example of illness. Usually when the damaged cells develop in the prostate gland occurs prostate cancer occurs. These cells increase uncontrollably. Reports given by the researchers show that this is …
Published in Journal of Computer Technology & Applications · Vol. 14, Issue 3, 2023 · pp. 1–9 Read article
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AI-Driven Prediction of Mechanical and Thermal Properties in Polymer-Based Functionally Graded Composites
Abstract: The proposed architecture of the current paper is an artificial intelligence (AI)-driven model of forecasting mechanical and thermal aspects of polymer-based functionally-graded composites (FGCs). Traditional micromechanical and finite element models, which are practical in homogeneous composites, might not be able to account in nonlinear interaction that is caused by compositional gradient. To overcome the challenge, machine learning (ML) models like artificial neural network (ANN), support vectors regression (SVR), and gradient-boosted …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 70–89 Read article