A Survey of Forex and Stock Price Prediction Using Deep Learning [PDF]
Applied System Innovation, 2021 Predictions of stock and foreign exchange (Forex) have always been a hot and profitable area of study. Deep learning applications have been proven to yield better accuracy and return in the field of financial prediction and forecasting.
Ze Hu, Yiqi Zhao, Matloob Khushi
semanticscholar +1 more source
Intelligence based Accurate Medium and Long Term Load Forecasting System
Applied Artificial Intelligence, 2022 In this study, we aim to provide an efficient load prediction system projected for different local feeders to predict the Medium- and Long-term Load Forecasting.
Faisal Mehmood Butt +7 more
doaj +1 more source
VAR, ARIMAX and ARIMA models for nowcasting unemployment rate in Ghana using Google trends
Journal of Electrical Systems and Information Technology, 2023 The analysis of the high volume of data spawned by web search engines on a daily basis allows scholars to scrutinize the relation between the user’s search preferences and impending facts. This study can be used in a variety of economics contexts.
Williams Kwasi Adu +2 more
doaj +1 more source
Mean Absolute Percentage Error untuk Evaluasi Hasil Prediksi Komoditas Laut
JOINS (Journal of Information System), 2020 Volume ekspor komoditas gurita mengalami kenaikan dan stok di suatu daerah akan tidak merata dan berlebih, serta bahwa permintaan gurita di beberapa negara tujuan di Asia, Eropa dan Amerika telah meningkat secara signifikan.
Ida Nabillah, Indra Ranggadara
semanticscholar +1 more source
Application of Artificial Neural Network to Solar Potential Estimation in Hilly Region of India [PDF]
Journal of Renewable Energy and Environment, 2022 The use of these conventional resources causes continuous depletion of fossil fuels and increased greenhouse effect. Solar power is the major renewable resource used for power generation across the globe.
Rahul Dogra, Sanjay Kumar, Nikita Gupta
doaj +1 more source
A comprehensive approach on predicting the crop yield using hybrid machine learning algorithms
Journal of Agrometeorology, 2022 Crop yield prediction is a complex task which uses historical data to predict how much yield can be obtained in a particular year. To predict accurate crop yield, a novel deep neural network named crop yield predicting deep neural network with XGBoost ...
KRITHIKHA SANJU SARAVANAN +1 more
doaj +1 more source
Mean absolute percentage error (MAPE) and error range for the four activity monitors tested irrespective of footwear type. [PDF]
, 2016 Mean absolute percentage error (MAPE) and error range for the four activity monitors tested irrespective of footwear type.
Orlaith Kilgannon (2742577) +7 more
core +1 more source
Aplikasi Triple Exponential Smoothing Untuk Forecasting Jumlah Penduduk Miskin
Jurnal Derivat, 2016 This study aims to predict the number of poor in Indonesia for the next few years using a triple exponential smoothing method. The purpose of this research is the result of the forecast number of poor people in Indonesia accurate forecast results are ...
Padrul Jana
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Improving Lettuce Fresh Weight Estimation Accuracy through RGB-D Fusion
Agronomy, 2023 Computer vision provides a real-time, non-destructive, and indirect way of horticultural crop yield estimation. Deep learning helps improve horticultural crop yield estimation accuracy. However, the accuracy of current estimation models based on RGB (red,
Dan Xu +3 more
doaj +1 more source
Mean absolute percentage error (MAPE) and error range for the four activity monitors tested: all values ± 2SD from the mean observed step count excluded. [PDF]
, 2016 Mean absolute percentage error (MAPE) and error range for the four activity monitors tested: all values ± 2SD from the mean observed step count excluded.
Orlaith Kilgannon (2742577) +7 more
core +1 more source