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45 articles for “economic forecasting”
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Using AIML to Enhance Demand Forecasting in Business
Abstract: Artificial intelligence machine learning (AIML) can play a significant role in enhancing demand forecasting in business. AIML is a programming language designed for creating chatbots and conversational agents, but its application extends beyond simple interactions. In the context of demand forecasting, AIML can be utilized to analyze historical data, customer interactions, and market trends. By implementing AIML algorithms, businesses can create intelligent models that learn from past demand patterns, customer …
Published in Journal of Computer Technology & Applications · Vol. 15, Issue 1, 2024 · pp. 35–40 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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Meanings from Ground Truth: A Related Affair to Consume
Abstract: Ground truth (GT) ever forms in three dimensional by eye. Similarities by instrumentations have subjected to perform by binocular stereopsis visions. Net visionary has descriptive issued to nodal communicating commands to subscribe communal. Linking messengers may be containment of any arena inform like nodal clusters of vector data to as form metadata to correspond selective issues. This has subjectively called planted data or synthetic communal data. Estimation of prompt informs …
Published in Journal of Mechatronics and Automation · Vol. 7, Issue 1, 2020 · pp. 17–23 Read article
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Stock Market Prediction Using Machine Learning: Techniques, Challenges, and Future Directions
Abstract: The continuous advancement of machine learning (ML) technologies has significantly transformed the field of financial forecasting, particularly in the area of stock market prediction. The ability to accurately forecast stock price movements and market trends plays a crucial role in supporting informed investment strategies and effective risk management. This paper provides a comprehensive review of recent developments in the application of ML techniques for predicting stock market behavior. It classifies …
Published in E-Commerce for Future & Trends · Vol. 13, Issue 1, 2026 · pp. 10–16 Read article
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Artificial Intelligence based Sustainable Decision Intelligence for Climate Action
Abstract: This paper proposes a Sustainable Decision Intelligence (SDI) framework to address the limitations of traditional climate policy through AI-driven analytics. By reviewing literature from 2020–2026, the study examines the impact of Artificial Intelligence (AI) on climate forecasting, energy optimization, and biodiversity monitoring, categorizing these tools into predictive, optimization, and policy intelligence layers. While acknowledging critical hurdles like data bias and computational energy costs, the research argues that integrating AI into …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 13, Issue 3, 2025 Read article
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Improving Supply Chain Resilience through Predictive Analytics and Real-Time Data Integration
Abstract: Demand forecasting has under gone major changes because to the incorporation of automated analytics into supply chain management (SCM), which has improved company productivity, accuracy, and responsiveness. Central to this transformation is the application of machine learning (ML), which enables the analysis of large and complex datasets to identify patterns, detect trends, and generate precise forecasts. Conventional methods for predicting frequently rely on linear models and historical sales data, which …
Published in International Journal of Industrial and Product Design Engineering · Vol. 3, Issue 2, 2025 · pp. 8–17 Read article
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Artificial Intelligence and Machine Learning Approaches for Corrosion Prediction and Management of Steel Reinforcement in Concrete: A Systematic Review
Abstract: Load bearing concrete structures need steel reinforcement bar (rebar), which are prone to attack by the corrosive environment inside the concrete due to constant ingress of moisture, pollutant gases and anions (mainly Cl−, SO42−). In recent models for the potential life span, the causes of failure of concrete structures have been established principally due to the chloride (Cl−) ion, because of the ease in transportation of Cl− in concrete and …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 13, Issue 3, 2025 Read article
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Short-Term Load Demand Forecasting using Chaos Theory and ANFIS
Abstract: In the electrical power sector, forecasting of load demand is an important process for effective planning of future expansion and periodical operations including unit commitments, fuel scheduling, short-term maintenance, security assessments, reducing spinning reserve, reliability analysis etc. Accurate load predictions are also necessary to utilize the electrical energy efficiently and to minimize the conflicts between the demand and supply of electricity. As electric load pattern of a region is very …
Published in Trends in Electrical Engineering · Vol. 6, Issue 2, 2016 · pp. 50–57 Read article
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Next-Gen Agriculture: Deep Learning Algorithms for Real-Time Plant Disease Detection via IoT
Abstract: In addition to providing high-quality food, the agriculture industry plays a critical role in supporting expanding people and economies. Plant diseases can have a detrimental effect on biodiversity and result in significant losses in food production. Automated methods for early and precise identification of plant diseases can reduce financial losses and enhance the quality of food produced. Deep learning has significantly improved object detection and picture classification accuracy in recent …
Published in Recent Trends in Sensor Research & Technology · Vol. 11, Issue 1, 2024 · pp. 18–23 Read article
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Imperishable Sewage treatment plant - A case study of Surat, India
Abstract: In the 21st century, it is prominently observed that there is a major contamination of water resources in particular fresh water resources due to increase in the municipal, agricultural and industrial wastes. Moreover, in today's world, environmental pollution has become a hot topic. Water is becoming increasingly scarce, and many people fear that future conflicts will be fought over pure drinking water. Water scarcity not only causes problems for humans, …
Published in Journal of Water Resource Engineering and Management · Vol. 9, Issue 3, 2022 · pp. 10–20 Read article
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Real-Time Analysis of E-Waste Monitoring Using Data Visualization in Power BI
Abstract: The exponential growth of electronic waste (e-waste) in India poses significant environmental and public health challenges, necessitating robust monitoring, management, and disposal strategies. This project, Real-time analysis of e-waste generated across different countries in the world and also survey report of India, seeks to provide a comprehensive assessment of e-waste production patterns, utilizing real-time data to capture dynamic shifts in waste generation and collection. By leveraging Power BI for advanced …
Published in Journal of Remote Sensing & GIS · Vol. 16, Issue 2, 2025 · pp. 1–7 Read article
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Strategies for Efficient Integration of Distributed Energy Resources into Microgrid Systems
Abstract: With the growing integration of Distributed Energy Resources into modern power systems, the global energy landscape is changing. Some of the DERs are solar photovoltaic (PV), wind turbines, battery storage systems, combined heat and power (CHP) units, and electric vehicles (EVs). Some of the advantages include lower transmission losses, better energy efficiency, and more resilience to grid failures. However, the far-reaching integration of DERs carries with it considerable technical, economic, …
Published in Journal of Power Electronics and Power Systems · Vol. 15, Issue 3, 2025 · pp. 51–56 Read article
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AI and Big Data for Optimized Water Resource Management in Arid Regions
Abstract: Water scarcity in arid regions is an escalating global challenge, driven by climate change, population growth, and increasing demands from urban, industrial, and agricultural sectors. Effective water resource management (WRM) is crucial for sustaining livelihoods, economic stability, and infrastructure resilience. Emerging technologies such as artificial intelligence (AI), machine learning (ML), and big data offer innovative solutions for optimizing water use, enhancing efficiency, and improving sustainability in water-scarce environments. This paper …
Published in Trends in Transport Engineering and Applications · Vol. 12, Issue 1, 2025 · pp. 1–5 Read article
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Techniques for Congestion Mitigation in Hybrid Electricity Markets
Abstract: In hybrid electricity markets, managing congestion is a crucial issue that impacts market efficiency, grid stability, and the integration ofrenewable energy sources. In orderto efficiently detect and manage crowded zones, this study suggests an enhanced congestion mitigation strategy by introducing the notion of Average Transmission Congestion Distribution Factor (ATCDF). In order to improve grid dependability, the research focuses on integrating Wind Power Generation (WPG) with Battery Energy Storage Systems (BESS) …
Published in Trends in Electrical Engineering · Vol. 15, Issue 3, 2025 · pp. 1–6 Read article
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Develop a Data Science Approach for Optimizing Energy Consumption
Abstract: Optimizing energy consumption has become a critical challenge in the era of sustainability and increasing energy demand. Efficient energy management is essential to address environmental concerns, reduce costs, and ensure resource availability for future generations. This project leverages data science techniques to evaluate and improve energy consumption across diverse sectors, including residential, industrial, and commercial domains. By integrating advanced analytics, machine learning models, and real-time data processing, the project aims …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 1, 2025 · pp. 31–44 Read article
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Information Technology: An Arising Concept in Agriculture Sector
Abstract: AbstractThe agriculture sector plays predominant role in economy of India. Information Technology is an important branch in the field of agriculture as it provides support to the farming community. Agriculture is the backbone of agro industries. IT contributing one third to the national GDP in the Indian economy. Under the changing dynamics of economical and industrial growth, agriculture has to experience changes with new approaches. The agricultural sector has to …
Published in Journal of Computer Technology & Applications · Vol. 4, Issue 1, 2013 · pp. 23–27 Read article
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Comparative Performance Study: Deterministic vs. Probabilistic Models in Retail Chains
Abstract: The finished goods, raw materials, and product stock that a business has on hand for sale are referred to as inventory. They enable the companies to achieve their sales levels and are a chance to cost control and decision making. It is a huge asset to a manufacturing firm. Inventory model permits forecasting of quantities of raw material, inventory and spare parts of the equipment to a very high level …
Published in Recent Trends in Mathematics · Vol. 2, Issue 1, 2025 · pp. 1–6 Read article
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Crop Yield Prediction Using Machine Learning Algorithm Based on Climate Variables
Abstract: India's economy is based primarily on agriculture, as over 50% of the country's population depends on it for their livelihood. The long-term viability of agriculture is seriously threatened by variations in the weather, climate, and other environmental factors. Because machine learning provides tools for decision assistance in agricultural yield prediction, including guidance on which crops to plant and when to plant them during the growing season, it is essential to …
Published in International Journal of Cheminformatics · Vol. 1, Issue 2, 2023 · pp. 49–52 Read article
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Forecasting Climate-Driven Healthcare Demand in Agricultural Regions: A Multi-Modal AI Approach
Abstract: The rapidly increasing instability of world climatic regimes has made past meteorological thresholds irrelevant, especially in the agricultural areas where monetary stability and well-being of humans are closely intertwined with an environmental situation. The more the frequency of 1 in every 1000-year events, i.e., heatwaves and catastrophic flooding increase, the greater the rural healthcare systems are in crisis, i.e., unable to predict a surge in demand because of data scarcity, …
Published in International Journal of Climate Conditions · Vol. 2, Issue 2, 2025 · pp. 28–38 Read article
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Green Q-Commerce: Balancing Speed and Sustainability in Hyper-Fast Delivery Systems
Abstract: The rapid expansion of quick commerce (q-commerce) has transformed consumer expectations with ultra-fast deliveries, yet its environmental impact—marked by carbon-intensive logistics, excessive packaging waste, and energy-heavy operations—poses significant sustainability challenges. This review examines how the q-commerce sector can reconcile speed with ecological responsibility through innovative solutions, including electrified last-mile delivery (e-bikes, electric vehicles, drones), circular packaging models (reusable containers, biodegradable materials), and artificial intelligence (AI)-driven logistics optimization (route efficiency, demand …
Published in E-Commerce for Future & Trends · Vol. 12, Issue 2, 2025 · pp. 22–27 Read article