Multiple households very short-term load forecasting using bayesian networks
Load forecasting is essential for different activities on power systems, and there is extensive
research on approaches for forecasting in different time horizons, from next-hour to decades …
research on approaches for forecasting in different time horizons, from next-hour to decades …
[PDF][PDF] Sensitivity of MAPE using detection rate for big data forecasting crude palm oil on k-nearest neighbor
Forecasting involves all areas in predicting future events. Many problems can be solved by
using a forecasting approach to become a study in the field of data science. Forecasting that …
using a forecasting approach to become a study in the field of data science. Forecasting that …
The effect of a SECoS in crude palm oil forecasting to improve business intelligence
Crude palm oil is a crop that has a harvest period of±2 weeks and is in dire need of
dissemination of information using e-commerce in order to be able to predict the price of the …
dissemination of information using e-commerce in order to be able to predict the price of the …
Measuring the accuracy of simple evolving connectionist system with varying distance formulas
Abstract Simple Evolving Connectionist System (SECoS) is a minimal implementation of
Evolving Connectionist Systems (ECoS) in artificial neural networks. The three-layer network …
Evolving Connectionist Systems (ECoS) in artificial neural networks. The three-layer network …
Optimization of MSE Accuracy Value Measurement Applying False Alarm Rate in Forecasting on Fuzzy Time Series based on Percentage Change
Time series is a method of forecasting in which it is carried out on the previous data to obtain
future data. This study conducted forecasting on the price of gold, in which the process is …
future data. This study conducted forecasting on the price of gold, in which the process is …
Sensitivity of shortest distance search in the ant colony algorithm with varying normalized distance formulas
The ant colony algorithm is an algorithm adopted from the behavior of ants which naturally
ants are able to find the shortest route on the way from the nest to places of food sources …
ants are able to find the shortest route on the way from the nest to places of food sources …
CO2 Emissions Forecasting in Multi-Source Power Generation Systems Using Dynamic Bayesian Network
Climate change is one of the significant challenges that the planet is facing nowadays. CO 2
emission is the largest contributor, and it is mainly released by human activities. In Europe …
emission is the largest contributor, and it is mainly released by human activities. In Europe …
Adaptive neuro-fuzzy inference system for forecasting rubber milk production
RF Rahmat, S Sembiring… - IOP Conference Series …, 2018 - iopscience.iop.org
Natural Rubber is classified as the top export commodity in Indonesia. Its high production
leads to a significant contribution to Indonesia's foreign exchange. Before natural rubber …
leads to a significant contribution to Indonesia's foreign exchange. Before natural rubber …
Financial technology forecasting using an evolving connectionist system for lenders and borrowers: ecosystem behavior
Financial technology (FinTech) which is included in the development of digitalization in the
financial sector in the industrial era 4.0. FinTech can make any transactions anywhere with …
financial sector in the industrial era 4.0. FinTech can make any transactions anywhere with …
Crude Palm Oil Price Forecasting Based on ECoS-MARS: in Data Science Models
The crude palm oil (CPO) industry is highly competitive due to fluctuating and unpredictable
prices. To accurately predict future CPO prices, a forecasting technique is necessary. This …
prices. To accurately predict future CPO prices, a forecasting technique is necessary. This …