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544 articles for “predictive algorithm”
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Artificial Intelligence in Healthcare for Implants and Tissue Regeneration: Advances, Challenges, and Future Directions
Abstract: Artificial intelligence (AI) has been a revolutionary influence in contemporary healthcare, especially in implant design, biomaterials research, and tissue regeneration. In regenerative medicine, AI facilitates predictive modeling, optimization, and decision-making via the analysis of intricate biological, material, and clinical information. This study analyzes current research on AI applications in implant technologies and tissue regeneration, specifically addressing scaffold engineering, biomaterial characterisation, stem cell and gene treatments, smart biomaterials, and implant planning. …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 13, Issue 3, 2025 Read article
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User Personality: Prediction and Question Answering System
Abstract: Personality refers to the general traits of a person based on his or her psychological and individual characteristics that reflect into a person’s overall nature and behaviour. Among the featured measures of this system are the MBTI (Myers Briggs Personality Type) which divides individual personalities into 16 distinct types across four axes. To predict the personality of an individual to get a hint about the individual, a personality prediction system …
Published in Journal of Advancements in Robotics · Vol. 10, Issue 1, 2023 · pp. 5–17 Read article
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Predicting the Computer Access Needs of Employee Using Data Mining Algorithms
Abstract: Every business relies on data to better organize and access the information to improve their business operations and to identify opportunities for improvement. A better framework improves the ability to valuable products and better services to their customers. The wide swaths of data that every organization gathers requires a proper methodology to gain knowledge about the latest trends in the market. Data mining is the process that analyses the data …
Published in Journal of Advances in Shell Programming · Vol. 10, Issue 1, 2023 · pp. 12–16 Read article
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Exploring the World of Big Data: Understanding Impact and Possibilities
Abstract: Big data refers to the management and analysis of large and complex data sets that cannot be handled by traditional data processing software. It involves techniques for extracting useful information from these data sets, and involves challenges such as data storage, analysis, sharing, and privacy. The three main characteristics of big data are the large volume of data, the variety of data types, and the fast pace at which data …
Published in Recent Trends in Parallel Computing · Vol. 9, Issue 3, 2022 · pp. 36–41 Read article
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Machine Learning Approach to Predict the Mental Health Issues of Employees in Tech Companies
Abstract: Mental disorders are conditions that have an impact on your emotions, thoughts, and behaviour. It may happen infrequently or have a persistent effect. The topic of mental health has been major and challenging, especially for working professionals. Over time, the urbanized living and workload put a strain on people, making them more vulnerable to mental disorders like anxiety and mental disorders. Working professionals therefore seem to be at an elevated …
Published in Journal of Computer Technology & Applications · Vol. 13, Issue 3, 2022 · pp. 1–10 Read article
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Implementation of Anticipating Rainfall Using Machine Learning
Abstract: Rainfall forecasting is crucial for many aspects of our national economy and should help prevent major seasonal droughts. Since agriculture is a beloved profession in many states, some Asian countries are economically hooked to decline. Previous precipitation info is beneficial. Farmers are cancerous in managing their crops, resulting in economic progress for the country. downfall prediction is hard for earth science scientists because of unordering time and unordered quantity of …
Published in International Journal of Satellite Remote Sensing · Vol. 1, Issue 1, 2023 · pp. 1–8 Read article
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A Machine Learning Based Artificial Intelligence Model for Detecting Heart Illness
Abstract: This study centers around the improvement of an artificial intelligence- and computerized reasoning-based heart sickness determination framework. We exhibit how AI can help with foreseeing whether an individual will get cardiovascular infection. In this review, a Python-based application for medical care research is created since it is more reliable and helps track and lay out many kinds of well-being observing applications. We show information handling, which incorporates working with all …
Published in Journal of Computer Technology & Applications · Vol. 15, Issue 1, 2024 · pp. 50–58 Read article
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Efficient Energy Management using Artificial Intelligence (AI) and Machine Learning (ML) in Chemical Industry
Abstract: The globe is moving toward higher usage of renewable energy sources, particularly solar and wind energy, as a result of depleting fossil fuel supplies and growing environmental concerns. There are several forecasting methods available for effective wind energy utilization. This review uses algorithms for predicting solar and wind energy as well as artificial intelligence (AI) techniques. A wind-coal coupling energy system planning scheme was designed to lower the high energy …
Published in Journal of Modern Chemistry & Chemical Technology · Vol. 16, Issue 2, 2025 · pp. 33–50 Read article
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Estimating the Chances of Winning IPL Match using Machine Learning
Abstract: Cricket is a popular sport not only in India but across the world. In recent years, the T-20 variant of this game has become extremely popular. The Indian Premier League (IPL), one of the championships associated with this format, has grown rapidly. On the other hand, cricket has long been considered a high-risk sport. Predicting the winner of the tournament or the game has an area of concern for many …
Published in Journal of Software Engineering Tools & Technology Trends · Vol. 9, Issue 1, 2022 · pp. 28–36 Read article
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Real-time DDoS Attack Prediction in SDN Environments Using Machine Learning
Abstract: The ever-growing reliance on sdn-based services necessitates robust security measures against Distributed Denial-of-Service (DDoS) attacks that threaten service availability. This project investigates the development of a real-time prediction system for DDoS attacks in sdn environments, leveraging the power of machine learning. The proposed system employs a Decision Tree classification algorithm implemented in Python. To ensure accurate attack identification, the system meticulously addresses data preprocessing challenges inherent in network traffic datasets. …
Published in Journal Of Network security · Vol. 13, Issue 1, 2025 · pp. 16–27 Read article
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A Profound Analysis on Complex Multiclass BCI Signals Classification by an EEG Device
Abstract: With a major shift in the technology paradigm today in the area of deep learning and artificial intelligence, one of its important applications today is found in brain-computer interface (BCI). Brain computer-interface, also known as neural control interface or mind-machine interface is a device that helps a user to interact with a computer using only his brain-activity, which is measured usually by Electroencephalography (EEG). The usage of such mechanism has …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 8, Issue 1, 2021 · pp. 22–44 Read article
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Enhancing Mutual Fund Investment Decision-making Using Machine Learning: A Survey
Abstract: In India, a significant portion of individuals save a part of their income for a secure future. Government and various public sector financial companies also provide some saving schemes through banks, post offices, and Life Insurance Corporation (LICs) such as Recurring Deposit (RD), Public Provident Fund (PPF), Sukanya Samridhhi Account (SSA) fixed deposits, etc. Over the past decade, many individuals have shifted their saving schemes to vigorously searching for investment …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 2, Issue 1, 2024 · pp. 43–51 Read article
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Prediction of Solar Proton Events Occurrence using CMEs and Flares as Control Events
Abstract: Prediction of Solar Energetic Particle (SEP) events is an important research area and helps in enabling space scientists prevent the risks and hazards for the space assets and astronauts. Several methods have been developed for predicting SEP events by means of studying the measured Solar Proton Event (SPE) in conjunction with other remote and in-situ measurements. The supporting measurements include solar soft and hard x-ray data, radio measurements, sunspot numbers, …
Published in Research & Reviews : Journal of Space Science & Technology · Vol. 7, Issue 3, 2018 · pp. 26–34 Read article
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Performance, Combustion and Emission analysis of Sunflower oil based Biodiesel using Non-Dominated Sorting Genetic Algorithm-II
Abstract: Biodiesel is used as alternate fuel of I. C. Engines for so many years. It is obtained from various edible and non-edible oils including waste cooking oils through trans-esterification process in the presence of catalyst. The suitable amount of biodiesel mix with commercial diesel can be used to run the compression ignition engines. The optimum combination of engine input parameters is the challenging task as required by the design engineer …
Published in International Journal of Energy and Thermal Applications · Vol. 1, Issue 1, 2023 · pp. 1–6 Read article
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GenChrome-ML: A Machine Learning Framework for Early Detection of Chromosomal Disorders Using Genomic Data
Abstract: The increasing burden of chronic disease and cancer demands innovative, more rapid and effective diagnostic tools in the field of healthcare. The majority of current diagnostic tools are dependent upon clinical symptomology and manual evaluation, leading to delays in early detection and treatment. The development of artificial intelligence (AI) and machine learning (ML), in recent years, has offered opportunities for the enhancement of disease prediction, diagnosis and personalization of treatment …
Published in International Journal of Bioinformatics and Computational Biology · Vol. 4, Issue 2, 2026 Read article
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Defining Regression Polynomials with Process Similarity Criteria
Abstract: Highly accurate monitoring and prediction is essential in detecting abnormality events and forecasting demands in supply chains. This investigation provides a computational procedure for defining polynomials that satisfy similarity criteria in the monitoring process for a polynomial of any degree. It provides an example of using algorithms to predict transient thermal processes in electronic devices. The second-degree polynomial defined with this algorithm is compared with a polynomial defined using a …
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 10, Issue 2, 2023 · pp. 13–20 Read article
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Analysis of Disease and Risk Prediction using ML
Abstract: This paper comprises of efficient machine learning algorithms used in predicting diseases through symptoms. As, the health industry has a huge amount of data for various fields, so we want to make a system where we can use various other applications of machine learning on health industry. This all had been done to make better medical decisions and also for rise in the accuracy. As an accurate analysis and early …
Published in Journal of Multimedia Technology & Recent Advancements · Vol. 7, Issue 1, 2020 · pp. 7–13 Read article
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Stock Price Prediction Using Data Science Techniques
Abstract: This study centers around persuasively presenting the potential to forecast the stability of future market stocks. Previous research has delved into predicting the trajectory of future market trends, leading to fluctuations in stock data, which opens avenues for refinement. The proposed model employs data science methodologies to predict the stock price index's value. This is achieved by contrasting supervised classification data science learning algorithms that predict either stock price increases …
Published in E-Commerce for Future & Trends · Vol. 10, Issue 2, 2023 · pp. 33–41 Read article
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Wear and Tribological Characteristics of Novel Metal Matrix Composites
Abstract: The development of advanced metal matrix composites (MMCs) with enhanced tribological performance has become increasingly important due to the premature failure of critical engineering components operating under severe wear conditions in automotive, aerospace, marine, defense, and power generation systems. Conventional composites such as Copper–Alumina and Aluminium–Silicon Carbide have demonstrated improved mechanical and wear characteristics; however, their widespread application is often limited by issues including particle agglomeration, non-uniform reinforcement distribution, porosity …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 1326–1346 Read article
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AI-Based House Price Prediction
Abstract: The housing market is one of the most dynamic and significant sectors of any economy, influencing both individual wealth and broader economic stability. Buyers, sellers, investors, and policymakers all rely on accurate housing price predictions. With the advent of artificial intelligence (AI) technologies, particularly machine learning algorithms, the task of house price prediction has seen remarkable advancements. This study provides a detailed overview of AI-based techniques for house price prediction. …
Published in Current Trends in Signal Processing · Vol. 13, Issue 3, 2023 · pp. 1–7 Read article