Results 41 to 50 of about 1,892,513 (283)

PRAKIRAAN CURAH HUJAN KECAMATAN KAIRATU KABUPATEN SERAM BAGIAN BARAT DENGAN MODEL AUTOREGRESIVE INTEGRATED MOVING AVERAGE (ARIMA)

Barekeng, 2007
Forecasting is an activity to use the past data as the basic to predict the future event that will occur. The result from the prediction is an un-sure event or just a guess, but with some certain methods then the prediction will be more than a guess, it ...
Grace Loupatty
doaj   +1 more source

A multi-variable multi-step Seq2seq networks for the state of charge estimation of lithium-ion battery

Case Studies in Thermal Engineering, 2023
Due to the complexity and changeable of lithium-ion batteries, we propose a multi-variable and multi-step Temporal neural network to cover this task. Specially, a novel multi-step training strategy is applied to deal with long time sequences, and multi ...
Yufeng Huang, Jian Sun, Lei Xu
doaj   +1 more source

Forecasting of water intake and supply in water plant in Johor [PDF]

, 2021
The safety and availability of water are important for public health, domestic use, food, and drink production process. Since water is essential in daily life, the demand for water intake and water supply are increasing. Moreover, it must be ensured that
Azli, Nor Amiratun Najwa, Foo, Fong Ying, Nor, Maria Elena   +2 more
core   +1 more source

Evaluation of load forecasting using different models

Measurement: Energy
This paper addresses a new prediction of load technique that joins the adaptability of RNNs with the capabilities of temporal modelling of Kolmogorov–Arnold Recurrent with good accuracy, because in energy management, load forecasting is essential since ...
Saroj Kumar Panda, Bishwajit Dey
doaj   +1 more source

Cooperative prediction method of gas emission from mining face based on feature selection and machine learning

International Journal of Coal Science & Technology, 2022
Collaborative prediction model of gas emission quantity was built by feature selection and supervised machine learning algorithm to improve the scientific and accurate prediction of gas emission quantity in the mining face.
Jie Zhou, Haifei Lin, Hongwei Jin, Shugang Li, Zhenguo Yan, Shiyin Huang   +5 more
doaj   +1 more source

Using intelligent optimization methods to improve the group method of data handling in time series prediction [PDF]

, 2008
In this paper we show how the performance of the basic algorithm of the Group Method of Data Handling (GMDH) can be improved using Genetic Algorithms (GA) and Particle Swarm Optimization (PSO).
A. Episcopos, A.G. Ivakhnenko, D. Chappell, D.E. Goldberg, I. Hayashi, J.H. Holland, J.R. Koza, S.A. Billings   +7 more
core   +1 more source

An upstream open reading frame regulates expression of the mitochondrial protein Slm35 and mitophagy flux

FEBS Letters, EarlyView.
This study reveals how the mitochondrial protein Slm35 is regulated in Saccharomyces cerevisiae. The authors identify stress‐responsive DNA elements and two upstream open reading frames (uORFs) in the 5′ untranslated region of SLM35. One uORF restricts translation, and its mutation increases Slm35 protein levels and mitophagy.
Hernán Romo‐Casanueva, Ariann E. Mendoza‐Martínez, P. Abril Medina‐Flores, Carlos Campero‐Basaldua, Alexander DeLuna, Soledad Funes   +5 more
wiley   +1 more source

Comparative Analysis Using Multiple Regression Models for Forecasting Photovoltaic Power Generation

Energies
Effective machine learning regression models are useful toolsets for managing and planning energy in PV grid-connected systems. Machine learning regression models, however, have been crucial in the analysis, forecasting, and prediction of numerous ...
Burhan U Din Abdullah, Shahbaz Ahmad Khanday, Nair Ul Islam, Suman Lata, Hoor Fatima, Sarvar Hussain Nengroo   +5 more
doaj   +1 more source

Modeling Critical Flow through Choke for a Gas-condensate Reservoir Based on Drill Stem Test Data [PDF]

Iranian Journal of Oil & Gas Science and Technology, 2017
Gas-condensate reservoirs contain hydrocarbon fluids with characteristics between oil and gas reservoirs and a high gas-liquid ratio. Due to the large gas-liquid ratio, wellhead choke calculations using the empirical equations such as Gilbert may contain
Ahmad Lak, Reza Azin, Shahriar Osfouri, Rouhollah Fatehi   +3 more
doaj   +1 more source

IMAE for Noise-Robust Learning: Mean Absolute Error Does Not Treat Examples Equally and Gradient Magnitude's Variance Matters [PDF]

, 2020
In this work, we study robust deep learning against abnormal training data from the perspective of example weighting built in empirical loss functions, i.e., gradient magnitude with respect to logits, an angle that is not thoroughly studied so far ...
Clifton, David, Hua, Yang, Kodirov, Elyor, Robertson, Neil M, Wang, Xinshao   +4 more
core   +2 more sources