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224 articles for “Random Forest”
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Evaluating UX Design Factors Affecting Efficiency of Composite Material Design and Analysis Platforms
Abstract: Within engineering software platforms that involve the design, simulation and characterization of composite materials, user experience (UX) design has become a key determinant for efficient use. This research aims to quantify how user experience design parameters relate to productivity in composite engineering workflows by analyzing the relationship between usability, learnability, accessibility, complexity of the UI, navigation efficiency and users engineering results satisfaction. Computational techniques in python were used in the …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 · pp. 341–366 Read article
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A Hybrid Multi-Physics Ensemble Deep Learning Framework for Simultaneous Prediction of Thermal and Electrical Conductivity in Functional Polymer-Based Nanocomposites
Abstract: Polymer-based nanocomposites have become promising materials for applications in energy storage, flexible electronics, biomedical devices, aerospace components, and advanced engineering because of their tunable thermal and electrical properties. Reliable prediction of these properties is essential for accelerating material design; however, existing analytical models and conventional machine learning techniques often fail to represent the complex interactions among filler characteristics, polymer matrices, processing conditions, and interfacial transport phenomena. This work presents HMEP-Net, …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 1062–1082 Read article
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A Review of AI-Based Intrusion Detection Systems for Mobile Ad Hoc Networks (MANETs)
Abstract: Mobile Ad Hoc Networks (MANETs) comprise wireless networks that lack any conventional infrastructure . Their chief features include highly changing network topologies, lack of centralized administration, and open nature of communication, which collectively result in making MANETs of the wireless kind very susceptible to a diverse range of cyber-attacks like blackhole, greyhole, wormhole, flooding, Sybil and denial-of-service (DoS) among others. Conventionally, Intrusion Detection Systems (IDS) relying on static rule-based methods …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 13, Issue 3, 2025 Read article
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Predicting Dielectric Constants of Polymers Using Molecular Structural Descriptors and Explainable Machine Learning: A Data-Driven Approach
Abstract: Accurate prediction of dielectric constants in polymeric materials is fundamental to the rational design of advanced electronic components, energy storage capacitors, flexible substrates, and high-frequency communication circuits. Conventional approaches to identifying suitable polymer dielectrics rely on extensive experimental synthesis and characterisation, which are both time-consuming and resource-intensive. In this work, an explainable machine learning framework is developed to predict the dielectric constant of polymers directly from molecular structural descriptors derived …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 297–304 Read article
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DISEASE PREDICTION SYSTEM USING MACHINE LEARNING
Abstract: Machine learning (ML) is a rising field. It already plays an important role in many fields, with projects of all sizes showing its positive impact. One such use of machine learning algorithms is in the healthcare field. Medical facilities need to be improved in order to make better decisions about patient diagnosis and treatment options. In this paper, we attempt to use the performance of Machine learning equipment in health …
Published in Journal of Control & Instrumentation · Vol. 12, Issue 2, 2021 · pp. 14–18 Read article
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Soft Computing Based Prediction of Deviator Stress of Waste Plastic Reinforced Sand
Abstract: In the recent past, the soft computing techniques have received a significant attention for solution of the geotechnical stability problems. Following the trend, the present study tries to explore the use of different soft computing techniques such as random forest regression, support vector machines (SVM) RBF kernel, SVM poly kernel and M5P model tree for the prediction of deviator stress of sand reinforced with waste plastic strips. The deviator stress …
Published in Journal of Geotechnical Engineering · Vol. 6, Issue 3, 2019 · pp. 1–7 Read article
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Mining Educational Data to Analyze Students‟ Performance
Abstract: Data Mining Strategy can be utilized in various fields to extricate the necessary information from the huge dataset. One of the useful fields of data mining is education. It is useful in educational field so that a pattern can be generated from the data. Placement of a student in graduation plays a very important role in the life of a student. Prediction whether the student will be able to get …
Published in Journal of Instrumentation Technology & Innovations · Vol. 11, Issue 3, 2021 · pp. 11–16 Read article
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Liver Patient Analysis Using Machine Learning
Abstract: Liver, a critical inside organ of the human body whose chief errands are to take out created squander delivered by our life form, digest food, and safeguard nutrients and energy materials. The liver problem can cause different deadly infections, including liver malignant growth. Early conclusion, and treating the patients are necessary to diminish the gamble of those deadly sicknesses. As the finding of liver illness is costly and refined, various …
Published in Journal of Instrumentation Technology & Innovations · Vol. 12, Issue 2, 2022 · pp. 29–35 Read article
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Electric Vehicle Range Prediction
Abstract: The introduction of new energy vehicles has emerged as a new trend in the automotive industry inresponse to growing energy and environmental issues. The electric vehicle (EV) is the driving force behind newenergy vehicles. The one major problem electric vehicles have always been the distance(range) of the travel and mapto the nearby charging stations. For range prediction in the present study, four machine learningalgorithms—multiple linear regression, random forest regression, polynomial …
Published in Trends in Electrical Engineering · Vol. 13, Issue 3, 2023 · pp. 24–32 Read article
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Sentiment Analysis on Financial News Using Deep Learning Algorithm
Abstract: Sentiment analysis is the technique of computationally figuring out and categorizing reviews or comments expressed in a bit of textual content, especially a good way to decide whether or not the writer's mind-set in the direction and also very helpful to identify the customer’s opinion about the particular product or content. It is one of the active and wanted research areas in natural language processing. In existing work, machine learning …
Published in Journal of Computer Technology & Applications · Vol. 12, Issue 1, 2021 · pp. 24–27 Read article
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Predicting diabetes status using ensemble algorithms with hyperparameter tuning
Abstract: Diabetes is a condition in which the body is unable to produce enough insulin to keep blood sugar levels under control. If diabetes is not properly identified and treated, it can lead to kidney failure, nerve damage, blindness, and coronary heart disease. A healthy lifestyle, therefore, depends on the early identification of diabetes diseases. However, it can be difficult to assess a person's diabetic status if they live in remote …
Published in Research and Reviews : Journal of Computational Biology · Vol. 12, Issue 2, 2023 · pp. 1–9 Read article
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AI-Optimized Biodegradable Polymer Composites for Medical Applications
Abstract: The value of biodegradable polymer composites in the medical practice has been massive as the composites may be deployed to provide temporary structural support, and they are also safe to degrade within the human body. However, the conventional material design process is trial and error, which is ineffective and inefficient. The article proposes a hybrid model involving experimental characterization, as well as an artificial intelligence (AI)-based model, to optimize biodegradable …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 Read article
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Machine Learning–Assisted Design of High-Performance Biomedical Polymer Composites
Abstract: The high-performance biomedical polymer composite design needs to represent a trade-off between the strength, biocompatibility, and degradation that cannot be accomplished using conventional design methods. The study aims to develop a predictive and optimization framework of composite properties with the help of machine learning. The methods include ANN, SVM, Random Forest, and Gradient Boosting with experiment and simulation data. The results of Gradient Boosting show that the accuracy is 95.9 …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 Read article
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Digital Twin Assisted Intelligent Prediction of Polymer Composite Degradation Under Environmental Exposure
Abstract: Polymer matrix composites (PMCs) deployed in aerospace, marine, automotive, and renewable-energy structures are continuously subjected to coupled environmental stressors — ultraviolet (UV) radiation, moisture ingress, thermal cycling, and mechanical loading — that progressively degrade their mechanical performance. Conventional accelerated ageing tests and empirical lifetime models are time-consuming, destructive, and poorly suited to in-service, asset-specific degradation forecasting. This paper proposes a Digital Twin (DT) assisted intelligent prediction framework that fuses a …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 Read article
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Advances in Lung Cancer Detection and Diagnosis: An Integrative Approach Using Computational Chemistry, Statistics, Bioinformatics, Artificial Intelligence, and Machine Learning
Abstract: Lung cancer is still one of the most common and lethal cancers globally, accounting for more than a million deaths each year. Prompt detection is important, and imaging techniques like chest X-rays, MRIs, PETs, CTs, and molecular imaging have become important tools. But still, even though all these techniques do not provide an accurate classification of the lesion, they have led to the development of computer-based high-resolution image analysis. Computer …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 13, Issue 2, 2026 Read article
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Data-Driven Machine Learning Approach for Vehicle Fuel Economy Prediction and Performance Monitoring Using Real-World OBD Data
Abstract: Modern passenger vehicles generate large volumes of operational data through On-Board Diagnostics (OBD) systems, enabling continuous observation of vehicle performance under real-world driving conditions. However, much of the existing research mainly analyses previously recorded data and does not provide predictive mechanisms for monitoring vehicle performance under dynamically varying operating conditions. This study presents an AI and machine learning–based method for predicting and monitoring real-world vehicle performance and fuel economy using …
Published in Trends in Machine design · Vol. 13, Issue 2, 2026 · pp. 47–66 Read article
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Physics-Informed Machine Learning and Multiscale Modeling for Structure–Property Quantification of Polymer Composites
Abstract: The growing need for light-weight, high strength, and sustainable polymer composites has led to the development of smart methods that enable accurate structural-property quantification and material design. However, conventional methods have been predominantly data-based, thus ignoring physical constraints as well as multi-scale interactions involving fiber, matrix, interface, and process parameters, leading to lower accuracy and poor robustness and interpretability of the models. In this study, a Cat Swarm Optimization-Tuned Physics-Informed …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 Read article
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Accessavior: AI-Driven Real-Time Adaptive Web Interfaces for Intelligent User Experiences
Abstract: As the web has become more diverse, many traditional, one-size-fits-all web accessibility solutions that must be configured manually have proven inadequate in meeting the needs of each user. This paper introduces “Accessavior”, which is an intelligent, behavioural pattern-driven accessibility framework that can automatically customize the personalization of web interfaces based on the interaction patterns of users. The proposed system will continuously track cursor behaviours such as cursor movements, keystroke characteristics, …
Published in Current Trends in Information Technology · Vol. 16, Issue 2, 2025 · pp. 14–22 Read article
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Enhancing Explainability in Machine Learning Based Spam Email Detection Using LIME and SHAP
Abstract: Spam emails represent a continual and irritating cybersecurity issue due to the fast expansion of cyberspace communication. These messages are unwanted and, in some cases, dangerous, such as phishing schemes, identity theft, and the propagation of malware. They cause severe financial and data security threats to individuals and organizations. Conventional spam detection techniques, such as rule-based spamming, blacklisting, and keyword classification, are techniques that find it difficult to match adaptive …
Published in Journal Of Network security · Vol. 14, Issue 2, 2026 · pp. 35–48 Read article
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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