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359 articles for “Informed decision-making”
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Entropy, Symmetry, and Data Fusion: Emerging Methods in Multi-Objective Decision- Making and Smart Systems
Abstract: In the era of intelligent technologies and data-driven systems, multi-objective decision-making (MODM) has become an essential aspect of managing complex environments such as smart cities, autonomous systems, and cyber-physical networks. As decision-making scenarios become increasingly dynamic and uncertain, there is a growing need for advanced methodologies that can handle diverse objectives, conflicting constraints, and incomplete information. This review highlights the emerging role of entropy, symmetry, and data fusion as foundational …
Published in Emerging Trends in Symmetry · Vol. 1, Issue 2, 2025 · pp. 44–49 Read article
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Time Series Sales Forecasting Using ARIMA Model
Abstract: Sales forecasting is a critical application in various industries and presents one of the most challenging problems worldwide. One method of prediction involves identifying patterns in historical data, where the outcome is known in advance and can be validated using more recent data. If a pattern consistently leads to the same outcome, it can be considered a genuine relationship. This method is highly flexible and can be utilized with diverse …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 2, Issue 1, 2024 · pp. 17–27 Read article
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Business Analytics in Today’s World by Coupling Machine Learning and Process Mining
Abstract: Process development and management communities have recently paid a lot of attention to research on machine learning and process mining methodologies. Indeed, these strategies allow for equally automatic process & activity discovery, making them high-value services that aid in the reuse of information to aid decision-making. This article presents a two-layer methodology for determining the most important process patterns to execute based on the design context. At the same time, …
Published in E-Commerce for Future & Trends · Vol. 8, Issue 3, 2021 · pp. 43–49 Read article
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Data-Driven Predictive Analytics and Decision- Making in FinTech Using MongoDB and High-Throughput Data Pipelines
Abstract: This paper examines the implementation of MongoDB and high-throughput data pipelines within the financial technology (FinTech) sector to drive data-informed predictive analytics and decision-making. The study focuses on the architectural components, scalability, and challenges of integrating NoSQL databases into real-time data ingestion and analytics pipelines. The transformative potential of these technologies in modern financial systems is highlighted through practical use cases such as fraud detection, credit scoring, and personalized financial …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 3, Issue 1, 2025 · pp. 1–15 Read article
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Adoption to Big Data Analytics: Privacy Issues and Integration of PPDM to overcome it
Abstract: AbstractIn this emerging era of technology, the amount of data being generated is massive. To deal with such a huge amount of data, development of big data analytics to extract valuable information for making marketing decision is gaining popularity. This data can be either structured, semi-structured or unstructured, so it is very difficult to process such rapidly growing and changing data with the conventional database techniques. As big data is …
Published in Journal of Computer Technology & Applications · Vol. 8, Issue 2, 2017 · pp. 33–38 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 · pp. 21–29 Read article
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Career Counselling and Personality Assessment App
Abstract: From the early foundations of career counselling, the role of self-awareness in making informed career choices has been well recognized. Frank Parsons, widely regarded as the pioneer of career counselling, emphasized the necessity of understanding oneself to make wise career decisions. He proposed that this self-awareness should be systematically connected to job requirements and opportunities through logical reasoning and structured analysis. This approach aims to empower individuals to make well-informed …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 2, 2025 · pp. 63–69 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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Seismic Analysis of Conventional, Hexagrid and Octagrid Steel Structural Systems
Abstract: The seismic resilience of multi-story buildings in earthquake-prone regions is a critical consideration in structural engineering. This dissertation presents a comprehensive analysis of the seismic performance of proposed multi-story buildings with varying heights (G+10, G+15, and G+20) using conventional, hexagrid, and octagrid structural systems. The study utilizes the Response Spectrum Method under seismic zone Ⅴ conditions to assess key parameters including storey drift, storey displacement, base shear, and overturning moment. …
Published in Journal of Structural Engineering and Management · Vol. 11, Issue 1, 2024 · pp. 26–41 Read article
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Social Media Analysis Using Big Data
Abstract: Social media has become an essential aspect of everyday life across different age groups, serving functions ranging from sharing personal updates to staying informed about social developments. Our objective is to harness big data to extract meaningful insights from the immense and ever-expanding volume of data generated on social media platforms. We will collect and analyze data from various social media sources, including text, images, and user interactions, using cutting-edge …
Published in Journal of Advanced Database Management & Systems · Vol. 11, Issue 3, 2024 · pp. 35–46 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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Integration of Electronic Health Records EHR for Seamless Patient Care in India
Abstract: The integration of Electronic Health Records (EHR) represents a pivotal advancement in enhancing healthcare delivery in India. Electronic Health Record (EHR) systems are designed with the primary objective of centralizing, organizing, and digitizing patient-related data. By creating a unified digital platform, EHRs enable healthcare providers to easily access and share critical medical information across different departments, institutions, and geographical locations. This streamlined flow of data ensures that healthcare professionals are …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 14, Issue 2, 2024 Read article
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FutureGen – Predicting Genetic Health
Abstract: FutureGen is an intelligent web-based system developed to help couples assess the risk of genetic disorders in their future child through data-driven analysis. The system brings together modern web technologies and machine learning to offer accurate and accessible predictions. The frontend, built with React, provides an intuitive interface for user interaction, while a Flask-based backend API handles model inference and manages communication with the Supabase database, which securely stores user …
Published in International Journal of Genetic Modifications and Recombinations · Vol. 4, Issue 1, 2026 · pp. 23–35 Read article
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Comparative Study on Methods for Teeth Image Recognition
Abstract: This article proposes a new method to find a specific tooth from the digital picture of multiple teeth. The modified methods can significantly simplify the pattern recognition process for teeth. Here we compared some of the popular recognition method like principal component analysis (PCA) and hybrid differential method (HDM). These methods are lot more simple, runs faster and the identification rate is better. These approaches will reduce the traditional reliance …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 1, Issue 3, 2014 · pp. 22–31 Read article
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Design and Implementation of a Framework for Travel Package Recommendations
Abstract: AbstractTravel package recommendations are very important research area as the recommendations can help travellers to make well-informed decisions. The rationale behind this is that travel packages that are suitable for particular trip or travel can provide many benefits to travellers. In the recent past, tourism became an important source of income to many public and private sectors. Therefore, governments are taking special interest on providing tourism facilities. Travel package refers …
Published in Current Trends in Information Technology · Vol. 7, Issue 2, 2017 · pp. 11–16 Read article
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A novel similarity measure for interval value picture fuzzy Environment and extended TOPSIS
Abstract: Correct decision-making is the most arduous task in our daily life. The decisions are hard to make in the multi-criteria decision-making (MCDM) problems due to ambiguous and unexpected information. In order to cope with such uncertainties in the data, a new decision-making approach has been developed using a newly defined similarity measure under the framework of interval-valued picture fuzzy set (IVPFS), as an extension of picture fuzzy sets (PFS). In …
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 11, Issue 1, 2024 · pp. 1–10 Read article
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Grey relational fractional programming and cross-evaluating method for multi-attribute decision making problem in spherical fuzzy setting
Abstract: To apply the spherical fuzzy sets(SFSs) for multiple attribute decision making (MCDM) problems have the more realistic significance, because of the assessment data specified by experts are mostly fuzzy and uncertain, the uncertainty and vagueness, ambiguity and subjectivity of the information in an intricate decision making environment, In this paper, a method to acquire attribute weights of interval number form by using the maximization method of the grey relational relative …
Published in Research & Reviews : Journal of Statistics · Vol. 12, Issue 3, 2023 · pp. 40–52 Read article
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Development of an Integrated System Prototype to Improve Decisions in Land Use Planning and Management in Ethiopia, Hawzen
Abstract: Constitutional land use planning provides a means of legal control over changes in land use and provides an opportunity to allocate land use to areas best suited to that activity. However, since land use planning is not surveying properly and essentially only deals with suggestions to improve land use system. Land use planning and resource management is a challenging task to many developing countries, due to limited technical resource. Currently …
Published in Journal of Remote Sensing & GIS · Vol. 8, Issue 1, 2017 · pp. 41–52 Read article
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A Data-Driven Analysis of Machine Learning Classification Models for Reliable Crop Yield Prediction
Abstract: The adoption of ML technologies in agriculture is reshaping farming practices, empowering producers to make informed, data-oriented decisions that improve yields, sustainability, and long-term resilience. In mango cultivation, ML analyzes data from weather, soil, and pests to optimize irrigation, fertilization, and pest control. Predictive analytics help forecast ideal farming practices, minimizing resource wastage and improving yield. Real-time monitoring and image-based disease detection allow timely interventions to maintain plant health and …
Published in Research and Reviews : Journal of Crop science and Technology · Vol. 15, Issue 1, 2026 · pp. 12–17 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