Automatic design of machine learning via evolutionary computation: A survey
Abstract Machine learning (ML), as the most promising paradigm to discover deep
knowledge from data, has been widely applied to practical applications, such as …
knowledge from data, has been widely applied to practical applications, such as …
Evolutionary computation for expensive optimization: A survey
Expensive optimization problem (EOP) widely exists in various significant real-world
applications. However, EOP requires expensive or even unaffordable costs for evaluating …
applications. However, EOP requires expensive or even unaffordable costs for evaluating …
Evolutionary deep learning: A survey
As an advanced artificial intelligence technique for solving learning problems, deep learning
(DL) has achieved great success in many real-world applications and attracted increasing …
(DL) has achieved great success in many real-world applications and attracted increasing …
A two-stage estimation of distribution algorithm with heuristics for energy-aware cloud workflow scheduling
Y Xie, XY Wang, ZJ Shen, YH Sheng… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
With the enormous increase in energy usage by cloud data centers for handling various
workflow applications, the energy-aware cloud workflow scheduling has become a hot …
workflow applications, the energy-aware cloud workflow scheduling has become a hot …
A meta-knowledge transfer-based differential evolution for multitask optimization
Knowledge transfer plays a vastly important role in solving multitask optimization problems
(MTOPs). Many existing methods transfer task-specific knowledge, such as the high-quality …
(MTOPs). Many existing methods transfer task-specific knowledge, such as the high-quality …
Learning-aided evolution for optimization
Learning and optimization are the two essential abilities of human beings for problem
solving. Similarly, computer scientists have made great efforts to design artificial neural …
solving. Similarly, computer scientists have made great efforts to design artificial neural …
Distributed differential evolution with adaptive resource allocation
Distributed differential evolution (DDE) is an efficient paradigm that adopts multiple
populations for cooperatively solving complex optimization problems. However, how to …
populations for cooperatively solving complex optimization problems. However, how to …
Enhanced multi-task learning and knowledge graph-based recommender system
In recent years, the m ulti-task learning for k nowledge graph-based r ecommender system,
termed MKR, has shown its promising performance and has attracted increasing interest …
termed MKR, has shown its promising performance and has attracted increasing interest …
Quantum Behaved Particle Swarm Optimization‐Based Deep Transfer Learning Model for Sugarcane Leaf Disease Detection and Classification
T Tamilvizhi, R Surendran… - Mathematical …, 2022 - Wiley Online Library
Plant diseases pose a major challenge in the agricultural sector, which affects plant
development and crop productivity. Sugarcane farming is a highly organized part of farming …
development and crop productivity. Sugarcane farming is a highly organized part of farming …
A multipopulation multiobjective ant colony system considering travel and prevention costs for vehicle routing in COVID-19-like epidemics
As transportation system plays a vastly important role in combatting newly-emerging and
severe epidemics like the coronavirus disease 2019 (COVID-19), the vehicle routing …
severe epidemics like the coronavirus disease 2019 (COVID-19), the vehicle routing …