International Journal of Electrical, Energy and Power System Engineering
Universitas Riau · Indonesia
Aims & Scope
The International Journal of Electrical, Energy and Power System Engineering (IJEEPSE) is a journal published by the Department of Electrical Engineering, Universitas Riau. The journal aims to provide a platform to publish high-quality articles in electrical engineering and related areas. Its scope covers research in Power System Engineering, Telecommunication and Network Engineering, and Computer Science and Information Technology, which include but are not limited to the following topics: Power System Engineering Artificial Intellegence in Power System, Electric Power Generation, Transmission and Distribution, Electric Vehicles, Electrical Engineering Materials, Electrical Measurements, Energy Conservation, Energy Storage system, High Voltage Engineering, Power Economic, Power Electronics, Power Quality, Power System Planning, Power System Protection, Power System Stability and Control, Renewable Energy and Integration, Smart Grid. Telecommunication and Network Engineering Antenna and Wave Propagation, Artificial Intellegence in Telecomunication System, Communication Electronics and Microwave, Communication Network and Systems, Modulation and Signal Processing for Telecommunication, Network Management and Protocols, Network Security, Optical Communication, Radar Image Processing, Wireless and Mobile Communications. Computer Science and Information Technology Augmented/Virtual Reality, Artificial Intelligence, Big Data, Cloud Computing, Computer Network and Distributed Systems, Cybersecurity, Data Mining, Data Science, Human-Computer Interaction (HCI), Information Systems, Internet of Things (IoT), Mobile Application, Multimedia and Game Technology, Robotics and Embedded Systems, Software Engineering and DevOps, User Interface/User Experience (UI/UX).
General Information
Submission Info
Ethics & Quality
Think.Check.Submit Compliance
Based on the Think.Check.Submit framework by DOAJ, COPE & OASPA. All data from verified open sources.
Subject Classification
Research Topics (OpenAlex)
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