Search
45 articles for “economic forecasting”
-
Fractional Riemannian Fuzzy C-Means with Time-Series Regularization for Economic Manifold Forecasting
Abstract: A fractional Riemannian fuzzy c-means framework is proposed for uncertain economic forecasting on non-Euclidean data domains. Observations are represented on a Riemannian manifold, cluster centres are intrinsic prototypes, and a latent fuzzy regime signal is regularised by both autoregressive and fractional-memory penalties. The resulting objective couples geometric clustering with time-series consistency, thereby discouraging partitions that are locally plausible but temporally incoherent. Closed-form membership updates, exponential-map centre updates, normal equations for …
Published in Recent Trends in Mathematics · Vol. 3, Issue 2, 2026 · pp. 49–55 Read article
-
Performance Forecasting in Solo Sports: Leveraging Psychometrics, Economic Analysis, and Cultural Insights for Predictive Excellence
Abstract: The science of performance forecasting in solo sports has transcended traditional metrics, embracing a multidisciplinary approach. This paper explores the integration of psychometrics, economic analysis, and cultural insights to predict athletic success. By leveraging psychological profiling, economic factors, and cultural dynamics, this study aims to establish a comprehensive model for forecasting athlete performance with heightened accuracy. In the realm of solo sports, where individual prowess dictates success, traditional performance forecasting …
Published in Recent Trends in Sports · Vol. 1, Issue 1, 2024 · pp. 35–44 Read article
-
Visualizing And Forecasting Stocks Using Single Page Application
Abstract: In the fields of finance and economics, stock price forecasting is a vital and crucial subject. The stock market is not governed by any significant rules that may be used to anticipate or estimate the price of a stock. In an effort to forecast the price in the stock market, several techniques are employed, including technical analysis, fundamental analysis, time series analysis, statistical analysis, etc. However, none of these techniques …
Published in Journal of Electronic Design Technology · Vol. 13, Issue 2, 2022 · pp. 23–28 Read article
-
Forecasting Commodity Prices Using Deep Learning Techniques: An Empirical Evidence from India
Abstract: Commodity price forecasting is instrumental in financial markets, providing framework for investment choices and risk management practices. Traditional models, including statistical and machine learning approaches, have limitations in capturing the nonlinear and volatile nature of commodity prices. Deep learning (DL) techniques have emerged as promising alternatives, leveraging advanced neural networks to enhance predictive accuracy. This study presents a thorough and comprehensive examination of deep learning applications in commodity price prediction, …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 3, 2025 · pp. 08–12 Read article
-
CIPHER Intelligence: AI-Powered Global Military Expenditure Analysis and Predictive Modeling
Abstract: Military expenditure analysis has emerged as a critical component of economic and geopolitical intelligence in the modern era. This paper presents CIPHER Intelligence, a comprehensive AI-powered platform for analyzing and predicting global military spending patterns across 211 countries spanning54 years (1970-2024). We employ advanced machine learning techniques, particularly Random Forest regression models, to achieve 99.5% prediction accuracy for military expenditure forecasting based on economic indicators. The platform integrates data from …
Published in Research & Reviews : Journal of Statistics · Vol. 15, Issue 1, 2026 · pp. 1–8 Read article
-
Evaluating Advancements and Identifying Research Gaps in Automotive Spare Parts Demand Forecasting
Abstract: The automotive industry, a key driver of global economic activity, relies heavily on the effective management of spare parts to ensure vehicle longevity and reliability. Accurate prediction of demand for these components is imperative to uphold ideal stock levels, minimize expenditures, and elevate customer contentment. This review of literature assesses recent progressions in demand prediction methodologies for automotive spare parts, with a specific emphasis on conventional statistical methods and contemporary …
Published in Journal of Computer Technology & Applications · Vol. 15, Issue 3, 2024 · pp. 47–58 Read article
-
Applicability of SWMM Model for Urban Flood Forecasting: A Review
Abstract: Urbanization, the major goal for the emerging economies, with which come the major concerns, flood conditions being one of them. The huge losses of infrastructure and lives have alarmed us with the need to tackle this situation in an effective and sustainable manner. Flood forecasting and its management is the only sail through the narrow gap between the disasters and prosperity. Precipitation is the major component of the hydrologic cycle …
Published in Journal of Water Resource Engineering and Management · Vol. 4, Issue 2, 2017 · pp. 1–4 Read article
-
Modeling the Socioeconomic Factors Impact on Household Trip Production for Baghdad
Abstract: In Baghdad, the number of vehicles has increased more than two folds after 2003. The land use in many sectors has changed and expansions of residential zone are noticeable at other sectors while the restrictions on car ownership and commerce are nil. The restrictions on using many streets due to security issues cause a huge traffic jam among the whole network. It was felt that revision to the transportation policies …
Published in Trends in Transport Engineering and Applications · Vol. 2, Issue 3, 2015 · pp. 61–73 Read article
-
PV-Syst based Performance Forecasting of Grid Connected Solar PV System in Indian Scenario
Abstract: The presentation and economy of a solar photovoltaic framework relies upon area and geographic parameters. Anticipating energy productivity is significant for effective arranging and assessment rates. The proposed examination investigates the exhibition assessment of three interconnected geologically associated photovoltaic solar frameworks. In Jaipur, Kolkata and Chennai have been trying a 1 MW solar PV framework for a year. Recreations were performed utilizing PV Syst (a product device created by the …
Published in Trends in Electrical Engineering · Vol. 10, Issue 2, 2020 · pp. 33–39 Read article
-
Very Short-Term Load Forecasting Using Gaussian Process Regression
Abstract: Very Short-Term Load Forecasting (VSTLF) is critical for real-time grid stability, frequency control, and economic dispatch. This study proposes a Gaussian Process Regression (GPR)-based framework for one-hour-ahead load forecasting using hourly data from January 2020 to April 2024 for Delhi, India. The model incorporates meteorological data such as temperature, humidity, and dew point with lagged load values. The research takes into account time-related dependencies and seasonal changes in order to …
Published in Trends in Electrical Engineering · Vol. 16, Issue 1, 2025 · pp. 91–104 Read article
-
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
-
A review of the intelligent techniques for load forecasting of UHBVNL
Abstract: The primary aim of load forecasting is to know the change in power demand with the variable factors on a short-term, medium-term, and long-term basis and to evolve our power system network according to the changing variables. It ensures correct values to the operations, stability, demand management, scheduling generating capacity, efficiency, reliability, accuracy, economy, controlling, scheduling, security analysis, environmental sustainability, etc. Various forecasting techniques are there which are making it …
Published in Journal of Power Electronics and Power Systems · Vol. 13, Issue 3, 2023 · pp. 30–38 Read article
-
Comparative Study of Aggregate and Disaggregate Traffic Forecasting Technique for Industrial Corridor: Case Study of Vadodara District
Abstract: AbstractTransportation occupies a prominent place in modern life and its impact is spread in all domains of life. Transport planning is a discipline to study problems rising while planning transport facilities at urban, regional or national level and to prepare efficient basis for providing such facilities. Aim of transport planning at regional level is provision of connectivity and circuity with other regions as well as for expansion of existing facility …
Published in Trends in Transport Engineering and Applications · Vol. 5, Issue 1, 2018 · pp. 14–21 Read article
-
Computer Data Processing and Empirical Economics
Abstract: This is an article on empirical economics and computer data processing that discusses how computational technology have changed empirical research methods. It analyses how computer systems have changed data management, statistical modelling, and econometric analysis, focussing on large-scale data processing, algorithmic efficiency, and repeatability. Forecasting, policy simulation, and panel data analysis are key uses. The paper also addresses data quality, computational, and ethical issues in economic data use. The paper …
Published in Research & Reviews : Journal of Statistics · Vol. 15, Issue 1, 2026 · pp. 09–20 Read article
-
Assessing Air Quality, Climate Change, and Migration Dynamics in Delhi NCR: A System Dynamics Approach
Abstract: As climate change accelerates and environmental degradation worsens, urban centers like Delhi NCR are under increasing pressure from internal migration. Poor air quality—especially in rural and peri-urban regions—emerges both as a driver of out-migration and a deterrent for in-migration to already burdened cities. This study develops a system dynamics (SD) model that integrates climate variables, air pollution metrics, economic indicators, governance quality, and migration behavior to simulate population flows into …
Published in Recent Trends in Mathematics · Vol. 2, Issue 1, 2025 · pp. 7–11 Read article
-
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
-
To Study About Forecasts of Low-Cost Housing in India
Abstract: The paper presents chip away requiring little to no effort and economical elective structure materials having preferences on regions, for example, India where cement or steel lodging is expensive. The undertaking tends to the difficulties and pigeonholes of utilizing these materials as a basic segment for minimal effort lodging and their equivalent volume for adjustment to the expansive range of elements—physical, biological, social, monetary and specialized—through various foodstuffs created which …
Published in Journal of Industrial Safety Engineering · Vol. 6, Issue 2, 2019 · pp. 14–20 Read article
-
Second Wave COVID-19 Predictions and Forecasting of Confirmed Cases in West Bengal Using ARIMA Model
Abstract: Infection and death rates surged drastically during the second wave of the COVID-19 (called delta variant) in India, owing to the destructive virus. As our country's economic load makes it more difficult to control the measures and it is critical for states such as West Bengal to forecast future cases. The present study introduced a time series forecasting model aimed at predicting and forecasting the number of confirmed and active …
Published in Research and Reviews : A Journal of Immunology · Vol. 13, Issue 1, 2023 · pp. 1–8 Read article
-
Study of Social Trends Prediction Using AI
Abstract: AI (Artificial Intelligence) has fundamentally changed the ability to analyze social trends by using large datasets to develop predictions about human behavior, public sentiment, and global events. Using methodologies such as Natural Language Processing (NLP), Time-Series Forecasting, and Graph-Based Social Network Analysis, AI is able to find hidden correlations in a variety of available datasets, from social media to economic indicators to public records, and fundamentally changes decision-making based on …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 3, 2025 · pp. 19–29 Read article
-
A Thorough Examination of How Artificial Intelligence is Affecting the Transformation of Agriculture in India and Throughout the World
Abstract: By providing creative ways to increase crop yields, maximize resource usage, and advance sustainability, artificial intelligence (AI) is revolutionizing agriculture. AI technologies, such as machine learning, computer vision, and robotics, are being increasingly used in precision farming, crop monitoring, disease detection, and decision-making as the global agricultural sector faces pressing challenges like food security, population growth, and climate change. AI enables farmers to make data-driven decisions, optimize irrigation systems, monitor …
Published in Research & Reviews : Journal of Agricultural Science and Technology · Vol. 14, Issue 3, 2025 · pp. 39–45 Read article