Sign inSubmit
Tips: “quotes” for a phrase · author:Lee · a DOI goes straight to its article

109 results for “Time series analysis”

Set a search alert
Research ArticleOpen accessIn the keywordsPrediction on Land Market Value Based on the Real Estate Market in USALei WangThe Land Market Value, defined as the total value of land price and quantity data are derived from data on housing values, is an important factor in the estimation of structure costs using price indexes for housing and construction costs. In this study, we gather and analyze 34 years' national data on past and present real estate transaction. According to … …Journal of Mathematics and Statistics, Vol. 13, Issue 2 · 23 May 2017 · 7,555 accessesView PDFCite
Research ArticleOpen accessIn the keywordsForecasting and Modelling Electricity Demand Using Anfis PredictorM. Mordjaoui, B. BoudjemaProblem statement: Load forecasting plays an important task in power system planning, operation and control. It has received an increasing attention over the years by academic researchers and practitioners. Control, security assessment, optimum planning of power production required a precise short term load forecasting. Approach: This study tries to combine neural network and fuzzy logic for next week electric load … …Journal of Mathematics and Statistics, Vol. 7, Issue 4 · 14 Sep 2011 · 7,811 accessesView PDFCite
Research ArticleOpen accessIn the keywordsA VAR Model for Forecasting Land Market Value in USALei WangForecasts of the future tendency of economic variables such as GDP, inflation rate and unemployment rate, arise many interests from business and government. Also, Modeling the land market at the national level can capture rich dynamic presenting in interdependent economies. In this paper, we studied a Vector Auto-regression (VAR) of Land Market Value and five US macroeconomic variables. We employed … …Journal of Mathematics and Statistics, Vol. 14, Issue 1 · 1 Jan 2018 · 7,639 accessesView PDFCite
Research ArticleOpen accessIn the abstractSmart Weather Data Management System for Sustainable Agriculture in Maharashtra Using Machine LearningAishwarya V. Kadu, Kuraparthi Tirumala V. ReddyAgriculture will benefit greatly from efficient weather data sustainable management. Data can be utilized to schedule the prediction yield, crop growth, and irrigation. This paper collects real-time meteorological station data via APIs, primarily focusing on the weather data sustainable management system and data related to Maharashtra Wardha, India, which is involved in a live series period. Agriculture can make potential … …Journal of Computer Science, Vol. 21, Issue 7 · 7 Jul 2025 · 3,507 accessesView PDFCite
Research ArticleOpen accessIn the abstractSales Forecasting Models: Comparison between ARIMA, LSTM and ProphetDmitry BrykinSales forecasting is crucial for business planning and resource allocation. Data-driven approaches have become popular in this field. This study compares the performance of three forecasting models: Autoregressive Integrated Moving Average (ARIMA), Long Short-Term Memory (LSTM) and Prophet within the context of specific sales categories derived from acquiring data provided by a bank. This study uses a time series dataset … …Journal of Computer Science, Vol. 20, Issue 10 · 1 Aug 2024 · 7,981 accessesView PDFCite
Research ArticleOpen accessIn the abstractAn Intelligent Hybrid Machine Learning Model for Paddy Disease DetectionS. Hrushikesava Raju, S. Adinarayna, U. Sesadri et al.Most countries rely on paddy/rice as a preferred staple crop due to its desirable agronomic characteristics. However, during the growth cycle, undetected or delayed identification of diseases can significantly reduce crop yield. To address this, machine learning approaches are increasingly employed for early-stage disease detection. Traditional Recurrent Neural Networks (RNNs), while useful for sequential data, suffer from limitations such as … …Journal of Computer Science, Vol. 22, Issue 4 · 29 Apr 2026 · 1,747 accessesView PDFCite
Research ArticleOpen accessIn the abstractDiscrete to Continuous Algorithm for Optimal Channel Selection to Detect Alcoholism through EEG RecordingsHayat Sedrati, Wajih Rhalem et al.Alcoholism is a serious public health issue, and early diagnosis of this brain disease can be performed by analyzing Electroencephalogram (EEG) signals. However, the high dimensionality of EEG datasets requires significant computational time and resources for the automatic processing of EEG signals. This study proposes a novel method to reduce EEG dataset dimensionality using a Discrete to Continuous algorithm (DtC) … …Journal of Computer Science, Vol. 19, Issue 1 · 17 Jan 2023 · 5,904 accessesView PDFCite
Research ArticleOpen accessIn the abstractEffect of Domestic Consumption on GDP of Pakistan from 1981-2014Rabia Shaheen, Javeria Shabbir, He Shuquan, Khalid Mahmood MughalThe purpose of the study was to study the impact of domesticconsumption (electricity consumption, food, and natural gas) on the EconomicGrowth of Pakistan. Time series data is used for analysis from 1981 to 2014taken from the World Governance Indicators Index. Pakistan's GDP is used as adependent variable and household consumption includes consumption ofelectricity, food, and natural gas used as independent … …Journal of Social Sciences, Vol. 18, Issue 1 · 23 Aug 2022 · 6,376 accessesView PDFCite
Research ArticleOpen accessIn the abstractAn Empirical Investigation of the Pollution Haven-Halo Nexus in Eastern and Southern AfricaPaul KauluThis study looks into the relationship between trade and pollution in Eastern and Southern Africa from 1977 to 2016. This timeframe is particularly relevant as it was marked by rising CO₂ emissions despite major climate agreements such as the Kyoto Protocol (1997), Reducing Emissions from Deforestation and Forest Degradation (REDD+, 2007), as well as the Paris Agreement (2015). Using time-series … …American Journal of Environmental Sciences, Vol. 21, Issue 1 · 28 Jan 2026 · 2,917 accessesView PDFCite
Research ArticleOpen accessIn the abstractPredicting Support and Resistance Indicators for Stock Market with Fibonacci Sequence in Long Short-Term MemoryThambusamy Velmurugan, Thiruvalluvan IndhumathyPredictive data analytics is a branch of data analytics where models are designed that effectively interpret; anticipate outcomes by analyzing present data to make predictions about future. One of the major attributes for prediction is time and there have been a considerable number of time series analytical models that are used for forecasting. Long Short-Term Memory (LSTM) is a deep … …Journal of Computer Science, Vol. 16, Issue 10 · 28 Oct 2020 · 7,316 accessesView PDFCite