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106 articles for “Time series analysis”
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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 · 7,561 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 · 7,643 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 · 7,817 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 · 3,516 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 · 8,006 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 · 5,908 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 · 1,754 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 · 7,323 accessesView PDFCite
Research ArticleOpen accessIn the abstractDetermining Causes of Gully Erosion and Associated Rates of Change in South-East Nigeria, using a Remote Sensing and GIS MethodologySylvanus IroThe study of gully development on a regional scale is currently threatened by the intrinsic costs associated with steady field tracking and monitoring and the lack of historic measurements to perform time series analysis. The research objective is to develop a low-cost GIS and Remote Sensing methodology for monitoring and quantifying gully erosion and development over time, identifying the impact … …American Journal of Environmental Sciences, Vol. 16, Issue 5 · 22 Oct 2020 · 7,434 accessesView PDFCite
Research ArticleOpen accessIn the abstractECG Energy Change Study Based on Variational Mode DecompositionKai Dong, Lin Sun, Hongjun Xiong, Wenbo WangVariational Mode Decomposition (VMD) decomposes the signal into a series of Intrinsic Mode Type Functions (IMTFs) according with variational model and fluctuating characteristics of the signal itself, thus very suitable for the analysis of nonlinear and non-stationary Electrocardiogram (ECG) signal. Energy of ECG signal has certain distribution rules, but which could be affected by diseases; therefore, the study of ECG … …American Journal of Biochemistry and Biotechnology, Vol. 16, Issue 1 · 12 Mar 2020 · 7,403 accessesView PDFCite