Zobrazeno 1 - 10
of 16
pro vyhledávání: '"Emad Mabrouk"'
Autor:
Mohamed Saber, Tayeb Boulmaiz, Mawloud Guermoui, Karim I. Abdrabo, Sameh A. Kantoush, Tetsuya Sumi, Hamouda Boutaghane, Tomoharu Hori, Doan Van Binh, Binh Quang Nguyen, Thao T. P. Bui, Ngoc Duong Vo, Emad Habib, Emad Mabrouk
Publikováno v:
Geomatics, Natural Hazards & Risk, Vol 14, Iss 1 (2023)
AbstractThis study aims to examine three machine learning (ML) techniques, namely random forest (RF), LightGBM, and CatBoost for flooding susceptibility maps (FSMs) in the Vietnamese Vu Gia-Thu Bon (VGTB). The results of ML are compared with those of
Externí odkaz:
https://doaj.org/article/98a4a8db9d114887a06ffa1f7769f6ff
Publikováno v:
IET Systems Biology, Vol 15, Iss 5, Pp 148-162 (2021)
Abstract The minimum dominating set (MDSet) comprises the smallest number of graph nodes, where other graph nodes are connected with at least one MDSet node. The MDSet has been successfully applied to extract proteins that control protein–protein i
Externí odkaz:
https://doaj.org/article/3062903744924e19947075cfe7050207
Publikováno v:
Sensors, Vol 20, Iss 12, p 3509 (2020)
In wireless sensor/ad hoc networks, all wireless nodes frequently flood the network channel by transmitting control messages causing “broadcast storm problem”. Thus, inspired by the physical backbone in wired networks, a Virtual Backbone (VB) in
Externí odkaz:
https://doaj.org/article/1b1e3bfe7bea443cbd5f42ac90a3675b
Autor:
Tetsuya Sumi, Emad Mabrouk, Hamouda Boutaghane, Mohamed Saber, Tayeb Boulmaiz, Karim I. Abdrado, Mawloud Guermoui, Sameh A. Kantoush, Daisuke Nohara
Publikováno v:
Geocarto International. 37:7462-7487
This study presents two machine learning models, namely, the light gradient boosting machine (LightGBM) and categorical boosting (CatBoost), for the first time for predicting flash flood susceptibi...
Publikováno v:
2022 11th International Conference on Renewable Energy Research and Application (ICRERA).
Publikováno v:
Electronics; Volume 11; Issue 7; Pages: 982
The foundation of machine learning is to enable computers to automatically solve certain problems. One of the main tools for achieving this goal is genetic programming (GP), which was developed from the genetic algorithm to expand its scope in machin
Publikováno v:
Journal of Computational Science. 31:111-125
This paper introduces an automatic strategy for the segmentation of medical images from Magnetic Resonance Imaging (MRI) and Computed Topography (CT). A new segmentation technique is proposed to combine a new evolutionary algorithm, called the Immune
Publikováno v:
Processes
Volume 9
Issue 7
Processes, Vol 9, Iss 1187, p 1187 (2021)
Volume 9
Issue 7
Processes, Vol 9, Iss 1187, p 1187 (2021)
The integration of solar energy in smart grids and other utilities is continuously increasing due to its economic and environmental benefits. However, the uncertainty of available solar energy creates challenges regarding the stability of the generat
Publikováno v:
Scopus-Elsevier
For centuries, the study of prime numbers has been regarded as a subject of pure mathematics in number theory. Recently, this vision has changed and the importance of prime numbers has increased rapidly, especially in information technology, e.g., pu
TABU PROGRAMMING: A NEW PROBLEM SOLVER THROUGH ADAPTIVE MEMORY PROGRAMMING OVER TREE DATA STRUCTURES
Publikováno v:
International Journal of Information Technology & Decision Making. 10:373-406
Since the first appearance of the Genetic Programming (GP) algorithm, extensive theoretical and application studies on it have been conducted. Nowadays, the GP algorithm is considered one of the most important tools in Artificial Intelligence (AI). N