HSIC bottleneck based distributed deep learning model for load forecasting in smart grid with a comprehensive survey
Load forecasting is a vital part of smart grids for predicting the required electrical power
using artificial intelligence (AI). Deep learning is broadly used for load forecasting in the …
using artificial intelligence (AI). Deep learning is broadly used for load forecasting in the …
Evolution of industry and blockchain era: monitoring price hike and corruption using BIoT for smart government and industry 4.0
The price gouging or price hike is a worldwide issue, and it is related to inflation. Because of
rising prices, people in various countries cannot afford nutritious food or proper treatment …
rising prices, people in various countries cannot afford nutritious food or proper treatment …
Use of blockchain to prevent distributed denial-of-service (DDoS) attack: a systematic literature review
MR Alam, SI Khan, SBZ Chowa, AH Chowdhury… - Advances in Distributed …, 2023 - Springer
Abstract A Distributed Denial-of-Service (DDoS) assault overwhelms a server, network, or
service with Internet traffic, disrupting regular traffic. As the Internet becomes more …
service with Internet traffic, disrupting regular traffic. As the Internet becomes more …
[HTML][HTML] Malaysia energy outlook from 1990 to 2050 for sustainability: Business-as-usual and Alternative-policy Scenarios based economic projections with AI based …
Energy-outlook from past to future specific years has become essential in energy-economy.
Malaysia is a member of ASEAN (Association of South-east Asian Nations), and ASEAN is …
Malaysia is a member of ASEAN (Association of South-east Asian Nations), and ASEAN is …
Identifying COVID-19 pandemic stages using machine learning
Although the severity of COVID-19 has decreased in most of the countries, it remains a
threat that the world continues to tackle. Consequently, this paper presents a classification of …
threat that the world continues to tackle. Consequently, this paper presents a classification of …
DiGraph enabled Digital Twin and Label-Encoding Machine Learning for SCADA Network's Cyber Attack Analysis in Industry 5.0
N Al-Qirim, A Bani-Hani, M Majdalawieh… - IEEE Open Journal …, 2024 - ieeexplore.ieee.org
False-Data Injection Attack (FDIA), Remote-Tripping Command Injection (RTCI), and System
Reconfiguration Attack (SRA) on SCADA (Supervisory Control and Data Acquisition) …
Reconfiguration Attack (SRA) on SCADA (Supervisory Control and Data Acquisition) …
A Wireless Emergency Alerts System for Warning Disasters by Using Distributed Databases, GPS and Machine Learning Enabled API Services
As most disasters are weather-related, location tracking is crucial during any event, and
early warning systems can save lives. This article outlines the design and execution of a …
early warning systems can save lives. This article outlines the design and execution of a …
[PDF][PDF] HSIC bottleneck based distributed deep learning model for load forecasting in smart grid with a comprehensive survey
Load forecasting is a vital part of smart grids for predicting the required electrical power
using artificial intelligence (AI). Deep learning is broadly used for load forecasting in the …
using artificial intelligence (AI). Deep learning is broadly used for load forecasting in the …