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121 articles for “investment decisions”
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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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Fundamental Analysis of Mid-Cap Stocks in the Indian IT Sector
Abstract: Fundamental analysis is also needed for the classification of financial assets (stocks, bonds, and currencies) using economic indicators or valuation methods to determine their true value. The present study focuses on mid-cap stocks in the information technology (IT) sector of the Indian market, which includes sectors such as software development, hardware manufacturing, semiconductors, IT services, internet and e-commerce, telecommunications, cybersecurity, and cloud computing. Mid-cap stocks may offer a good mix …
Published in Current Trends in Information Technology · Vol. 15, Issue 1, 2025 · pp. 1–11 Read article
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Designing an AI-Based Platform for Stock Market Prediction
Abstract: The AI-Based Platform for Stock Market Prediction is an advanced tool designed to forecast stock prices and market trends using artificial intelligence. This platform combines machine learning algorithms, real-time financial data, and sentiment analysis to provide investors with actionable insights. The platform uses advanced predictive techniques like Long Short-Term Memory (LSTM) networks and Gradient Boosting Machines to generate precise and reliable forecasts. Additionally, it incorporates interactive visualizations and portfolio optimization …
Published in E-Commerce for Future & Trends · Vol. 12, Issue 3, 2025 · pp. 14–19 Read article
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Advancing Sustainability: A Comprehensive Review of Environmental, Social, and Governance (ESG) Practices
Abstract: Environmental, Social, and Governance (ESG) frameworks have emerged as critical pillars guiding sustainable business practices and responsible investment decisions. This review explores the multifaceted role of ESG principles in promoting environmental stewardship, advancing social equity, and ensuring ethical governance. Environmentally, ESG focuses on combating climate change, conserving biodiversity, and managing resources through renewable energy adoption, waste reduction, and carbon emission control. Socially, it emphasizes employee well-being, diversity, community engagement, and …
Published in Journal of Thermal Engineering and Applications · Vol. 12, Issue 2, 2025 · pp. 1–9 Read article
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Stock Market Analysis Using Data Science
Abstract: Stock market prediction using data science has become a popular area of research and application in recent years. This is because the stock market is a complex system with many variables and factors that affect its behavior, making it difficult to predict with certainty. The stock market has always been the aggression of buyers and sellers of stocks, therefore in the global finance market, stock trading is one of the …
Published in E-Commerce for Future & Trends · Vol. 11, Issue 1, 2024 · pp. 1–4 Read article
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Leveraging Industrial Waste for Green Sustainable Nanobiopolymer Synthesis: Polymer, Environmental, Legal and Global Arbitration Perspectives
Abstract: Nanobiopolymers can be synthesized from industrial waste using innovative methods, marking a forward-looking and ecologically sound step in production methods address to his Home State Industrial waste has been used conventionally either through incineration, landfilling or stabilization. It results in large environmental risks, including air, water and soil pollution and often involves costly stabilization and disposal. With the help of polymer and composite substance recovering value means life for current …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 705–711 Read article
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Linear Programming for Profit Optimization in Small-Scale Manufacturing: A Python-Based Simplex and Machine Learning Approach
Abstract: Profit maximization under resource constraints is a classic challenge. Small manufacturers face tight margins and scarce capital every day. This paper tackles that problem using four Python-based methods. The case study is Bintang Bakery in Bandar Lampung, Indonesia. The bakery makes three bread types and faces 18 resource constraints. Data comes from Anggoro et al. Methods tested include LP revised simplex, Differential Evolution, PSO, and ANN Surrogate. General-purpose scipy minimizers …
Published in Research & Reviews : Journal of Statistics · Vol. 15, Issue 2, 2026 · pp. 01–12 Read article
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Harnessing Machine Learning for Stock Movement Prediction: A Review of Current Approaches
Abstract: Stock price prediction is a crucial task in financial analysis, aiding investors and traders in making informed decisions. This study investigates the use of deep learning methods, particularly Long Short-Term Memory (LSTM) networks, for predicting stock prices based on historical market data. The dataset, sourced from Yahoo Finance, consists of time-series stock price data, which is preprocessed, feature-engineered, and visualized to improve prediction accuracy. The model's performance is assessed using …
Published in Journal of Advances in Shell Programming · Vol. 12, Issue 2, 2025 · pp. 29–40 Read article
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Determinants of Smallholder Farmers Quantity of Coffea arabica L., Supply to Market: A Case of Gimbo District, Kaffa Zone, Ethiopia
Abstract: This study investigates the factors influencing the market supply of coffee in various districts of the Gimbo District, Kaffa Zone, in Southwest Ethiopia. Coffee is Ethiopia's most significant export crop, recognized for its extensive genetic diversity and its substantial contribution to the country's GDP. Despite the district's strong production capacity, the marketing structure remains predominantly traditional, compelling producers to sell through conventional channels that do not offer premium prices, thereby …
Published in Research & Reviews : Journal of Agricultural Science and Technology · Vol. 14, Issue 3, 2025 · pp. 107–120 Read article
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Machine Learning Based House Price Forecasting
Abstract: This research endeavours to craft a predictive model leveraging machine learning to estimate the market value of houses in Delhi. By integrating Python and its powerful libraries, pandas for data processing, Plot for interactive visualizations, scikit-learn for implementing machine learning algorithms, XGBoost for boosting the model's prediction accuracy, and to evaluate the model's performance cross-validation techniques are used. An interactive user interface is created using a Flask web application to …
Published in Current Trends in Information Technology · Vol. 14, Issue 1, 2024 · pp. 5–11 Read article
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Predictive Modeling and Optimization of Tensile and Flexural Strength in FDM 3D Printing Using Decision Trees and Bayesian Optimization.
Abstract: This research investigates predictive modelling and optimization technique for the tensile and flexural strength of PlA (Poly Lactic Acid) in Fused Deposition Modelling (FDM) 3D printing. Employing Decision Trees and Bayesian Optimization enhances comprehension and control of 3D printing process. Precise model predicts PLA material properties based on input parameters. Methodology involves rigorous data preprocessing, encompassing, cleaning, transformation, and normalization. Hyperparameter optimization via grid search systematically explores configurations, optimizing model …
Published in Journal of Polymer & Composites · Vol. 11, Issue 12, 2023 · pp. 203–214 Read article
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House Price Estimation Using Linear Regression: A Machine Learning Perspective
Abstract: House price prediction plays a crucial role in the real estate industry, helping buyers, sellers, and investors make well-informed decisions. Accurate estimation of property values enables stakeholders to assess market trends, plan investments, and minimize financial risks. This study focuses on the application of linear regression, a fundamental and widely used machine learning algorithm, to predict house prices based on multiple influencing factors. These factors include location, property size, number …
Published in Research & Reviews : Journal of Statistics · Vol. 15, Issue 1, 2026 Read article
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AI-Based Intelligent Traffic Signal Management System: A Review
Abstract: Traffic congestion is a growing problem in urban areas worldwide, leading to economic losses, increased pollution, and commuter frustration. Traditional traffic management systems rely on fixed timing cycles and lack adaptability to real-time traffic conditions. Intelligent traffic light control systems based on artificial intelligence (AI) have become a viable substitute for traditional techniques. These systems are able to evaluate large volumes of traffic data in real time, identify patterns, and …
Published in International Journal of Electronics Automation · Vol. 3, Issue 2, 2025 · pp. 1–5 Read article
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AI and Access to Justice: An Indian Perspective
Abstract: Artificial intelligence is set to transform the legal profession, influencing everything from legal research and document review to legal advice and decision-making. This study investigates the possible uses of AI in the legal area, such as predictive analytics and AI-powered legal research tools. This study explains the role of AI in Judicial Systems. The study covers the related literature, challenges and opportunities in Indian judicial system. The usage of AI …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 3, Issue 2, 2025 · pp. 30–37 Read article
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The Daily Architect: A Personal Guide to Mastering Time and Building Productive Routines
Abstract: In today's fast-paced world, individuals face increasing challenges in managing their time, tasks, and personal responsibilities effectively. The concept of "My Daily Helper" is introduced as an intelligent, user-friendly system designed to streamline daily activities and enhance personal productivity. This research explores the design, functionality, and potential impact of such a digital assistant, emphasizing its role in task organization, time management, and decision support. The study investigates how a daily …
Published in Journal of Production Research & Management · Vol. 16, Issue 1, 2026 · pp. 37–50 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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Time Series Forecasting Based on PyAF and fbProphet
Abstract: Time series forecasting is the technique of predicting future events using previous data. Time series data includes information that is collected and recorded at regular intervals, such as daily stock prices, monthly sales figures, or hourly temperature readings. The purpose of time series forecasting is to use previous data to create accurate forecasts about the future values of a given variable. This can be beneficial for a range of applications, …
Published in International Journal of Information Security Engineering · Vol. 1, Issue 1, 2023 · pp. 32–36 Read article
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Artificial Intelligence in Diagnostics: Advancements, Challenges, and Future Prospects
Abstract: AI is changing (and will change) healthcare as we know it, and diagnostics might be the specialty that feels the most discomfort. Artificial intelligence-based analytical systems are facilitating the detection, diagnosis, and treatment of a variety of diseases, with better accuracy, speed, and results. Now, this abstract investigates the role of AI in diagnostics, scouring its elements, landmark techniques, transformative impact and future overview. This article explains AI and discusses …
Published in Research and Reviews: A Journal of Health Professions · Vol. 15, Issue 3, 2025 · pp. 8–17 Read article
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Comparative Analysis of Modern Programming Paradigms: Evaluating Language Efficiency and Compiler Design Technique
Abstract: This paper attempts to provide some insights into the efficiency of modern programming paradigms via a comparative study and explore the important role played by compiler design in the optimization of these languages. Programming languages have been evolving quickly over time and different paradigms: imperative, functional, or object-oriented programming come with their idiosyncrasies and optimization techniques. The study starts by defining the foundational principles of each paradigm. It then goes …
Published in Recent Trends in Programming languages · Vol. 11, Issue 3, 2024 · pp. 1–9 Read article
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Impact of Diet and Certain Functional Foods in Type-II Diabetes Management
Abstract: Global health is greatly challenged by type 2 diabetes mellitus (T2DM), whose management mostly depends on dietary and lifestyle changes. This review study looks at how important diet and certain functional items are for managing type 2 diabetes. It offers a thorough summary of current scientific discoveries and clinical investigations that emphasize the contribution of dietary decisions and functional foods to better glycemic control, increased insulin sensitivity, and decreased risk …
Published in Research & Reviews : Journal of Food Science & Technology · Vol. 13, Issue 1, 2024 · pp. 9–15 Read article