[HTML][HTML] Implication of machine learning techniques to forecast the electricity price and carbon emission: Evidence from a hot region

S Sarwar, G Aziz, AK Tiwari - Geoscience Frontiers, 2024 - Elsevier
The current study examines the significant determinants of electricity consumption and
identifies an appropriate model to forecast the electricity price accurately. The main …

Analysis of SARIMA Models for Forecasting Electricity Demand

A Aksöz, S Oyucu, E Biçer… - 2024 12th International …, 2024 - ieeexplore.ieee.org
This article presents an in-depth evaluation of electricity consumption predictions using the
Seasonal Autoregressive Integrated Moving Average (SARIMA) model. Leveraging …

Klasifikasi Kematangan Tanaman Hidroponik Pakcoy Menggunakan Metode SVM

L Priyambodo, HL Fuadi, N Nazhifah… - … (Rekayasa Sistem dan …, 2022 - jurnal.iaii.or.id
Pakcoy is a type of vegetable plant belonging to the Brassica family. Pakcoy plants can be
cultivated using hydroponic techniques, namely plant cultivation techniques without soil …

Empowering Sustainability: A Consumer-Centric Analysis Based on Advanced Electricity Consumption Predictions

HN Durmus Senyapar, A Aksoz - Sustainability, 2024 - mdpi.com
This study addresses the critical challenge of accurately forecasting electricity consumption
by utilizing Exponential Smoothing and Seasonal Autoregressive Integrated Moving …

An Adaptive Energy Orchestrator for Cyberphysical Systems Using Multiagent Reinforcement Learning†.

A Robles-Enciso, R Robles-Enciso… - … Cities (2624-6511 …, 2024 - search.ebscohost.com
Highlights: What are the main findings? A proof of concept of a smart energy management
system in a smart home. Using the reinforcement learning technique, we optimise energy …

Automated Approach to Selecting Neurological Medical Imaging Orders Using Natural Language Processing

V Mehta, R Dharia, N Desai - medRxiv, 2023 - medrxiv.org
Medical imaging, like computed tomography (CT) and magnetic resonance imaging (MRI),
holds profound value in disease diagnosis for millions worldwide. However, studies show …

Analyzing the Relationship Between Meteorological Parameters and Electric Energy Consumption Using Support Vector Machine and Cooling Degree Days …

NW Azizah, EY Puspaningrum… - Journal of Information …, 2024 - journal-isi.org
Nowadays, electricity is increasing rapidly. This increase is caused by several factors, one of
which is meteorological factors. Meteorological parameters have various types, but this …

[PDF][PDF] Imputation Missing Value to Overcome Sparsity Problems in The Recommendation System

S Lestari, ME Afdila, YA Pratama - Jurnal RESTI (Rekayasa Sistem …, 2023 - jurnal.iaii.or.id
A recommendation system is a system that provides suggestions or recommendations to a
product or service for its users. One of the problems encountered in the recommendation …

Multi scale prediction of electricity consumption using recurrent neural network specialty lndRNN

RT Khankook, M Banifakhr… - 2024 28th …, 2024 - ieeexplore.ieee.org
In recent years, with the rising global demand for energy, especially energy management
has become increasingly important. Electricity, regarded as one of the most vital energy …

Electricity consumption prediction based on Transformer-LSTM

L Qiao, S Chen, R Qu, R Ran, Y Guo… - 2023 3rd International …, 2023 - ieeexplore.ieee.org
The prediction of electricity consumption in the power system has always been an important
task in the management of the power department. Propose a regional electricity …