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543 articles for “predictive algorithm”
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Structure-Property Modeling and Engineering Optimization of Biodegradable Starch-Cellulose Biofoams for Sustainable Packaging
Abstract: Since the packaging industry is an engineered product with complex composites that involve a close relationship between composition, processing, and performance, optimization of formulation, cellular morphology, and engineering performance of biodegradable starch-based biofoams presents a considerable challenge. This study proposes a machine-learning-aided structure–property modeling framework to design and optimize starch-based biodegradable biofoams for sustainable packaging applications. A physics-informed synthetic dataset consisting of 10,000 formulations was created based on engineering relationships …
Published in Journal of Polymer & Composites · Vol. 14, Issue 5, 2026 Read article
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A MODEL TO PREDICT ANGULAR PHASE SHIFT BETWEEN WIND AND WAVES FOR FLOATING OFFSHORE WIND TURBINE APPLICATIONS
Abstract: This paper develops a model to predict angular phase shift between wind and waves that can be applied to floating offshore wind turbines. A theoretical simulation, developed in MATLAB program, has been run using non-linear effects that have led to specific algorithms based on matrix development of wind and waves direction. The modelling uses a random generator to create the wind and wave direction on the basis that the angular …
Published in Journal of Offshore Structure and Technology · Vol. 10, Issue 1, 2023 · pp. 1–12 Read article
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Adaptive E-Learning Algorithms and Heutagogy: A Systematic Analysis
Abstract: The proliferation of artificial intelligence (AI) and machine learning (ML) technologies has transformed the digital education landscape by enabling adaptive e-learning systems capable of personalizing content and optimizing learning paths. This study provides a systematic analysis of adaptive e-learning algorithms within the framework of heutagogy, an educational paradigm that emphasizes learner autonomy, self-direction, and capability development. The convergence of adaptive technologies with heutagogical principles offers new avenues for creating more …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 3, 2025 · pp. 33–38 Read article
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Non-Lethal Protection of Farmlands Against Wild Animals and Crop Estimation
Abstract: This paper is an integrated smart system that aims to enhance productivity related to agriculture along with agricultural safety through modern technology. Crop estimation system uses IoT sensors and machine learning algorithms for the analysis of real-time environmental data in terms of soil moisture, temperature, pH levels, and humidity. This data will further be used to provide the optimal crop for cultivation and appropriate fertilizer requirements for prediction of requirements. …
Published in Journal of VLSI Design Tools and Technology · Vol. 15, Issue 1, 2025 · pp. 18–24 Read article
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Data Mining Made Simple by A priori Algorithm for Market Analysis
Abstract: Data mining and data warehousing are increasingly becoming popular among IT professionals, academics and researchers from different disciplines. Business enterprises, small, medium or large scale, are considering the deployment of a warehouse as a major step and as a matter of pride. Data mining or knowledge discovery in data bases combines the techniques from mathematics, statistics, algorithms and artificial intelligence to extract the knowledge. Data mining is a main phase …
Published in Current Trends in Information Technology · Vol. 3, Issue 3, 2013 · pp. 1–4 Read article
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Farmer’s Pal
Abstract: Precision agriculture, characterized by data-driven decision-making, has transformed contemporary farming practices. To increase agricultural sustainability and efficiency, this abstract investigates the combination of sensor monitoring, machine learning, and picture processing. A network of sensors continuously collects vital environmental data, including temperature, humidity, rainfall, sunshine, soil moisture, and conductivity, for precision agriculture. By providing real-time insights, these sensors enable farmers to make informed choices about pest control, fertilization, and irrigation. This …
Published in Research & Reviews : Journal of Agricultural Science and Technology · Vol. 14, Issue 2, 2025 · pp. 19–31 Read article
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A Systematic Review on The Role of Artificial Intelligence in Assisted Reproductive Technology
Abstract: Artificial Intelligence (AI) has significantly transformed Assisted Reproductive Technology (ART) over the past five years, enhancing diagnostic accuracy, treatment personalization, and overall success rates. AI-driven algorithms and machine learning models have been integrated into various aspects of ART, including sperm selection, embryo grading, and predicting implantation success. Deep learning techniques have improved image-based embryo assessment, reduced human subjectivity and increased efficiency. Additionally, AI-powered predictive analytics have helped optimize ovarian stimulation …
Published in International Journal of Bioinformatics and Computational Biology · Vol. 4, Issue 1, 2026 · pp. 21–29 Read article
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A Comprehensive Review of Machine Learning and Explainable AI Techniques for Disease Prediction Systems
Abstract: Large amounts of diverse medical data have been produced because of the quick development of digital healthcare systems, offering substantial chances to use machine learning methods for clinical decision support and illness prediction. By identifying intricate patterns in clinical data, machine learning-based models have shown great promise in early disease detection, risk assessment, and personalised healthcare. However, issues with transparency, interpretability, and reliability have been brought up by the growing …
Published in International Journal of Biomedical Innovations and Engineering · Vol. 4, Issue 1, 2026 · pp. 20–28 Read article
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Role of Generative AI in Redefining Data Analytics
Abstract: The rapid evolution of data-driven technologies has introduced both significant challenges and promising opportunities within the field of data analytics. Among the most impactful advancements is Generative Artificial Intelligence (Generative AI), a groundbreaking subset of AI that is reshaping how data is interpreted, generated, and utilized. Unlike traditional analytical tools that rely solely on existing data patterns, generative AI possesses the capability to create synthetic data, simulate complex scenarios, and …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 3, Issue 2, 2025 · pp. 01–07 Read article
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IoT Sensors to Monitor Pipeline Pressure and Flow Rate Combined with ML-Algorithms to Detect Leakages
Abstract: In the field of fluid mechanics, pipelines are the lifeblood of industries, transporting everything from natural gas and oil to water and chemicals. Maintaining their integrity is paramount for safety, economic efficiency, and environmental protection. Traditional leak detection methods explained in fluid mechanics can be slow, expensive, and sometimes fail to identify small leaks early enough to prevent significant damage. However, the convergence of Internet of Things (IoT) and Machine …
Published in Recent Trends in Fluid Mechanics · Vol. 12, Issue 2, 2025 · pp. 40–48 Read article
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Eye Disease Classification Using K-means Clustering Algorithm and Ensemble Classification Approach
Abstract: In this study, we present a comprehensive approach for the classification of eye diseases, specifically targeting normal, cataract, glaucoma, and diabetic retinopathy conditions. This research uses a dataset from Kaggle, which provides a wide and varied collection of retinal images to ensure good representation. The methodology encompasses advanced image processing and machine learning techniques to ensure accurate diagnosis and prediction. The preprocessing phase involves a series of image enhancement techniques …
Published in International Journal of Bioinformatics and Computational Biology · Vol. 3, Issue 2, 2025 · pp. 15–27 Read article
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Smart HVAC Systems: The Role of IoT and AI in Energy Optimization
Abstract: Heating, ventilation, and air conditioning (HVAC) systems are crucial for maintaining interior comfort and air quality in all types of buildings. However, they also rank among the highest energy users in the built environment. Traditional HVAC systems are evolving into intelligent, networked systems through the integration of Internet of Things (IoT) and artificial intelligence (AI) technologies, as energy efficiency and sustainability become increasingly important across the globe. This review article …
Published in Journal of Refrigeration, Air conditioning, Heating and ventilation · Vol. 12, Issue 2, 2025 · pp. 38–43 Read article
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IoT Enabled Production Scheduling
Abstract: In the world of high competition between various firms; it is important that firms plan their production in advance. This will help them maximize the use of available resource and facilities. Production scheduling discusses the process of assigning an order to machines considering the total time available, required time, type of order and to arrange these orders in such way that machine idle time is minimized. By legitimate planning, firms …
Published in Journal of Production Research & Management · Vol. 8, Issue 3, 2018 · pp. 16–23 Read article
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Finding Churn Trend Scenario Using ML Techniques
Abstract: Abstract Media transmission and in addition the network access suppliers assumes an essential part in the mobile communications and the data society. Telecom segment is consistently developing with its progression in highlights and innovation. Consumer loyalty is an imperative factor which chooses the execution of firms. Customer churn expectation is an essential technique in CRM (Customer Relationship Management), knowing the churn propensity appeared by the customers helps to take better …
Published in Journal of Telecommunication, Switching Systems and Networks · Vol. 6, Issue 1, 2019 · pp. 1–8 Read article
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Integrative Machine Learning Approaches for Predicting the Rheological Behaviour of Soft Magnetorheological Elastomers
Abstract: Magnetorheological Elastomers (MREs) are advanced composite materials known for their ability to alter mechanical properties under external magnetic fields, making them highly valuable in adaptive damping systems, vibration control, and smart devices. The accurate prediction of rheological behavior in soft MREs remains a significant challenge due to the complex interplay between material composition and magnetic fields. To address this challenge, this study employs a multi-pronged approach that integrates traditional material …
Published in Journal of Polymer & Composites · Vol. 13, Issue 1, 2025 · pp. 1083–1096 Read article
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Exploring the Efficiency of Leading and Lagging Indicators in Algorithmic Trading
Abstract: This paper details a comparison of the overall performance of leading and lagging technical indicators used in algorithmic trading over an extended period. While much of the prior research focuses on index price forecasting and some on statistical arbitrage derived from these predictive techniques, there is a scarcity of studies that assess and evaluate trading strategies. The strategies considered for the study were tested on historical data of the 50 …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 2, Issue 2, 2024 · pp. 8–18 Read article
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Cybersecurity of AI and IoT Integrated for Mechanical Industries
Abstract: By facilitating the concept of Industry 4.0, the intersection of artificial intelligence (AI) and the Internet of Things (IoT) has changed the mechanical industries. When combined, these technologies are advancing process optimization, predictive maintenance, real-time condition monitoring, and smarter automation. In order to give proactive system control and intelligent decision-making, AI algorithms mine large datasets generated via IoT devices for relevant patterns. In the meanwhile, IoT guarantees smooth communication between …
Published in Journal of Mechatronics and Automation · Vol. 12, Issue 2, 2025 · pp. 27–33 Read article
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Knowledge discovery in software defect datasets using learning algorithms
Abstract: In this paper, the learning impact on various classification models were studied which were built using binary class-imbalanced data. Before the learning process, some preprocessing techniques were applied to training datasets for removing the redundancy. Nowadays feature selection and sampling techniques become an essential tool for many data mining task because learning algorithms do not perform well with defective datasets, dimensionality reduction problem arises. Sampling technique is also used to …
Published in Journal of Software Engineering Tools & Technology Trends · Vol. 5, Issue 2, 2018 · pp. 18–26 Read article
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Autonomous Scripting: The Future of AI-Enhanced Shell Programming for DevOps and Security
Abstract: The evolution of operating systems has seen a paradigm shift with the integration of artificial intelligence, quantum computing, and edge computing technologies. Autonomous scripting, driven by AI, is transforming DevOps workflows and security paradigms, enabling self-healing systems, predictive automation, and intelligent threat detection. This study explores the role of AI-enhanced shell programming in the automation landscape, discussing its implications for next-generation operating systems. It further delves into the integration of …
Published in Journal of Advances in Shell Programming · Vol. 12, Issue 1, 2025 · pp. 28–39 Read article
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Channel Prediction and Estimation Based on Machine and Deep Learning Techniques: A Review
Abstract: Channel prediction estimation in the high- speed mobile environment is a hot issue for 3D massive multiple input multiple output (MIMO) millimeter-wave (mmWave) system. In this environment, the channel has fast time-varying and non-stationary characteristics. And its time-domain correlation coefficient is a time- varying parameter, which makes it difficult for traditional channel estimation methods to capture the channel variations over time and achieve ideal channel estimation performance. A known signal, …
Published in Journal of Telecommunication, Switching Systems and Networks · Vol. 10, Issue 3, 2023 · pp. 13–17 Read article