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Multi-objective coyote optimization algorithm based on hybrid elite framework and Meta-Lamarckian learning strategy for optimal power flow problem
A multi-objective coyote optimization algorithm based on hybrid elite framework and Meta-Lamarckian learning strategy (MOCOA-ML) was proposed to...
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FalconNet: Factorization for the Light-Weight ConvNets
Designing light-weight CNN models with little parameters and Flops is a prominent research concern. However, three significant issues persist in the...
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A novel discrete ICO algorithm for influence maximization in complex networks
It is axiomatic that influence maximization is one of the major issues of the Internet today. In this paper a novel specialized metaheuristic...
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A modified harmony search algorithm and its applications in weighted fuzzy production rule extraction
Harmony search (HS) is a form of stochastic meta-heuristic inspired by the improvisation process of musicians. In this study, a modified HS with a...
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A stochastic multi-objective optimization method for railways scheduling: a NSGA-II-based hybrid approach
Optimizing resource utilization and train scheduling is essential to satisfy passengers and reduce operating costs. This study develops the train...
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Graph neural architecture search with heterogeneous message-passing mechanisms
In recent years, neural network search has been utilized in designing effective heterogeneous graph neural networks (HGNN) and has achieved...
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A knowledge-driven monarch butterfly optimization algorithm with self-learning mechanism
The Monarch Butterfly Optimization (MBO) algorithm has been proved to be an efficient meta-heuristic to directly address continuous optimization...
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An adaptive human learning optimization with enhanced exploration–exploitation balance
Human Learning Optimization (HLO) is a simple yet efficient binary meta-heuristic, in which three learning operators, i.e. the random learning...
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A graph-based framework for model-driven optimization facilitating impact analysis of mutation operator properties
Optimization problems in software engineering typically deal with structures as they occur in the design and maintenance of software systems. In...
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DEMFFA: a multi-strategy modified Fennec Fox algorithm with mixed improved differential evolutionary variation strategies
The Fennec Fox algorithm (FFA) is a new meta-heuristic algorithm that is primarily inspired by the Fennec fox's ability to dig and escape from wild...
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Bi-level decision making in techno-economic planning and probabilistic analysis of community based sector-coupled energy system
The paper proposes a bi-level programming model for community participation in techno-economic planning of an integrated energy system. Distribution...
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Dynamic Neural Networks for Adaptive Implicit Image Compression
Compression with Implicit Neural Presentations (COIN) is a neural network image compression method based on multilayer perceptron (MLP). COIN encodes...
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Harris hawks optimization based on global cross-variation and tent map**
Harris hawks optimization (HHO) is a new meta-heuristic algorithm that builds a model by imitating the predation process of Harris hawks. In order to...
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Meta-interpretive learning as metarule specialisation
In Meta-interpretive learning (MIL) the metarules, second-order datalog clauses acting as inductive bias, are manually defined by the user. In this...
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An ensemble algorithm based on adaptive chaotic quantum-behaved particle swarm optimization with weibull distribution and hunger games search and its financial application in parameter identification
Quantum-behaved Particle Swarm Optimization (QPSO) is a meta-heuristic optimization algorithm, which is widely used in many research fields and...
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Online Learning of Logic Based Neural Network Structures
In this paper, we present two online structure learning algorithms for NeuralLog, NeuralLog+OSLR and NeuralLog+OMIL. NeuralLog is a system that...
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A water cycle algorithm based on quadratic interpolation for high-dimensional global optimization problems
The water cycle algorithm (WCA) is easily trapped in local optimal solutions when dealing with high-dimensional optimization problems and has low...
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Automatic generation of atomic multiplicity-preserving search operators for search-based model engineering
Recently, there has been increased interest in combining model-driven engineering and search-based software engineering. Such approaches use...
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Visualisation of Numerical Query Results on Industrial Data Streams
The capability to efficiently handling and analysing data streams in industrial processes and industrial cyber-physical systems (ICPS) is critical...
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Modified Lévy flight distribution algorithm for global optimization and parameters estimation of modified three-diode photovoltaic model
Many real-world problems demand optimization, minimization of costs and maximization of profits, and meta-heuristic algorithms have proficiently...
