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Soft Computing for Smart Environments: Techniques and Applications
Faculty
Computer Science
Year:
2023
Type of Publication:
ZU Hosted
Pages:
280
Authors:
Mohammed Abdel Basset Metwally Attia
Staff Zu Site
Abstract In Staff Site
Journal:
1st Edition CRC Press
Volume:
Keywords :
Soft Computing , Smart Environments: Techniques , Applications
Abstract:
This book applies both industrial engineering and computational intelligence to demonstrate intelligent machines that solve real-world problems in various smart environments. It presents fundamental concepts and the latest advances in multi-criteria decision-making (MCDM) techniques and their application to smart environments. Though managers and engineers often use multi-criteria analysis in making complex decisions, many core problems are too difficult to model mathematically or have simply not yet been modeled. In response, as well as discussing AI-based approaches, Soft Computing for Smart Environments covers various optimization techniques, decision analytics, and data science in applying soft computing techniques to a defined set of smart environments, including smart and sustainable cities, disaster response systems, and smart campuses. This state-of-the-art book will be essential reading for …
Author Related Publications
Mohammed Abdel Basset Metwally Attia, "Discrete greedy flower pollination algorithm for spherical traveling salesman problem", Springer, 2019
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Mohammed Abdel Basset Metwally Attia, "A New Hybrid Flower Pollination Algorithm for Solving Constrained Global Optimization Problems", Natural Sciences Publishing Cor., 2014
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Mohammed Abdel Basset Metwally Attia, "A novel equilibrium optimization algorithm for multi-thresholding image segmentation problems", Springer London, 2021
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Mohammed Abdel Basset Metwally Attia, "An efficient binary slime mould algorithm integrated with a novel attacking-feeding strategy for feature selection", Pergamon, 2021
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Mohammed Abdel Basset Metwally Attia, "An efficient teaching-learning-based optimization algorithm for parameters identification of photovoltaic models: Analysis and validations", Pergamon, 2021
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Department Related Publications
Ibrahiem Mahmoud Mohamed Elhenawy, "BERT-CNN: A Deep Learning Model for Detecting Emotions from Text", Tech Science Press, 2021
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Ahmed Raafat Abass Mohamed Saliem, "BERT-CNN: A Deep Learning Model for Detecting Emotions from Text", Tech Science Press, 2021
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Ahmed Raafat Abass Mohamed Saliem, "Using General Regression with Local Tuning for Learning Mixture Models from Incomplete Data Sets", ScienceDirect, 2010
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Ahmed Raafat Abass Mohamed Saliem, "On determining efficient finite mixture models with compact and essential components for clustering data", ScienceDirect, 2013
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Ahmed Raafat Abass Mohamed Saliem, "Unsupervised learning of mixture models based on swarm intelligence and neural networks with optimal completion using incomplete data", ScienceDirect, 2012
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