[HTML][HTML] Methods of forecasting electric energy consumption: A literature review

RV Klyuev, ID Morgoev, AD Morgoeva, OA Gavrina… - Energies, 2022 - mdpi.com
Balancing the production and consumption of electricity is an urgent task. Its implementation
largely depends on the means and methods of planning electricity production. Forecasting is …

Data Mining Processes and Decision-Making Models in the Personnel Management System

SK Gupta, A Khang, P Somani, CK Dixit… - … Systems for Industry …, 2023 - taylorfrancis.com
Modern single and multiple economies rely on human capital to create useful services. The
processing and maintenance of the entire organization depend on the level of the person …

ML‐DDoSnet: IoT intrusion detection based on denial‐of‐service attacks using machine learning methods and NSL‐KDD

M Esmaeili, SH Goki, BHK Masjidi… - Wireless …, 2022 - Wiley Online Library
The Internet of Things (IoT) is a complicated security feature in which datagrams are
protected by integrity, confidentiality, and authentication services. The network is protected …

An optimization neural network model for bridge cable force identification

T Gai, D Yu, S Zeng, JCW Lin - Engineering Structures, 2023 - Elsevier
Accurate determination of cable force values is the most important technical means to avoid
damage to the cable bridge. In order to avoid the influence of the difficulty in distinguishing …

Predicting energy consumption of chiller plant using WOA-BiLSTM hybrid prediction model: A case study for a hospital building

Y Song, H Xie, Z Zhu, R Ji - Energy and Buildings, 2023 - Elsevier
It is important to study building energy consumption considering the current state of global
climate and its close relationship with building energy consumption. This study proposes a …

FDCNet: Presentation of the fuzzy CNN and fractal feature extraction for detection and classification of tumors

S Molaei, N Ghorbani, F Dashtiahangar… - Computational …, 2022 - Wiley Online Library
The detection of brain tumors using magnetic resonance imaging is currently one of the
biggest challenges in artificial intelligence and medical engineering. It is important to identify …

National strategy for climate change adaptability: a case study of extreme climate-vulnerable countries

N Arshed, MI Saeed, S Salem, U Hanif… - Environment …, 2023 - Springer
Countries face extreme climate-related adaptation challenges, but some countries are more
vulnerable due to their geographic location and socioeconomic conditions. These …

[HTML][HTML] A Review on Large-Scale Data Processing with Parallel and Distributed Randomized Extreme Learning Machine Neural Networks

E Gelvez-Almeida, M Mora, RJ Barrientos… - Mathematical and …, 2024 - mdpi.com
The randomization-based feedforward neural network has raised great interest in the
scientific community due to its simplicity, training speed, and accuracy comparable to …

[HTML][HTML] Hybrid attention-based temporal convolutional bidirectional LSTM approach for wind speed interval prediction

BS Bommidi, V Kosana, K Teeparthi… - … Science and Pollution …, 2023 - Springer
Precise wind speed prediction is crucial for the management of the wind power generation
systems. However, the stochastic nature of the wind speed makes optimal interval prediction …

[HTML][HTML] Prediction of peatlands forest fires in Malaysia using machine learning

L Li, A Sali, NK Noordin, A Ismail, F Hashim - Forests, 2023 - mdpi.com
The occurrence of fires in tropical peatlands poses significant threats to their ecosystems. An
Internet of Things (IoT) system was developed to measure and collect fire risk factors in the …