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Comparison of CLPSO, ECLPSO and ACLPSO on CEC2013 Multimodal Benchmark Functions
Particle swarm optimization (PSO) is a class of modern generalized intelligent optimization algorithms. Comprehensive learning PSO (CLPSO) is a...
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Black-winged kite algorithm: a nature-inspired meta-heuristic for solving benchmark functions and engineering problems
This paper innovatively proposes the Black Kite Algorithm (BKA), a meta-heuristic optimization algorithm inspired by the migratory and predatory...
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A hybrid swarm optimization with trapezoidal and pentagonal fuzzy numbers using benchmark functions
In this paper, a Hybrid Swarm Optimization algorithm is developed with Pentagonal Fuzzy Numbers (PFN) and Trapezoidal Fuzzy Numbers (TFN). We have...
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Evaluating the performance of meta-heuristic algorithms on CEC 2021 benchmark problems
To develop new meta-heuristic algorithms and evaluate on the benchmark functions is the most challenging task. In this paper, performance of the...
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Bugs in machine learning-based systems: a faultload benchmark
The rapid escalation of applying Machine Learning (ML) in various domains has led to paying more attention to the quality of ML components. There is...
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An Extended Jump Functions Benchmark for the Analysis of Randomized Search Heuristics
Jump functions are the most-studied non-unimodal benchmark in the theory of randomized search heuristics, in particular, evolutionary algorithms...
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Performance Analysis of Selected Evolutionary Algorithms on Different Benchmark Functions
This paper analyses and compares four recently published state-of-the-art evolutionary algorithms on three different sets of benchmark functions. The...
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Benchmark: Remaining Useful Life Predictor for Aircraft Equipment
We propose a predictive maintenance application as a benchmark problem for verification of neural networks (VNN). It is a deep learning based...
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Benchmark: Object Detection for Maritime Search and Rescue
We propose an object detection system for maritime search and rescue as a benchmark problem for verification of neural networks (VNN). The model to...
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WATB: Wild Animal Tracking Benchmark
With the development of computer vision technology, many advanced computer vision methods have been successfully applied to animal detection,...
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Topology optimization of a benchmark artifact with target stress states using evolutionary algorithms
Additive manufacturing enables extended freedom in designing structural components. In order to reduce manufacturing costs, the product quality has...
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CurveML: a benchmark for evaluating and training learning-based methods of classification, recognition, and fitting of plane curves
We propose CurveML, a benchmark for evaluating and comparing methods for the classification and identification of plane curves represented as point...
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A Cross-Platform Benchmark for Interval Computation Libraries
Interval computation is widely used in Computer Aided Design to certify computations that use floating point operations to avoid pitfalls related to...
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CGWO: An Improved Grey Wolf Optimization Technique for Test Case Prioritization
AbstractThe convergence rate has been widely accepted as a performance measure for choosing a better metaheuristic algorithm. So, we propose a novel...
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A machine learning surrogate modeling benchmark for temperature field reconstruction of heat source systems
The temperature field reconstruction of heat source systems (TFR-HSS) with limited monitoring sensors in thermal management plays an important role...
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Does it work outside this benchmark? Introducing the rigid depth constructor tool
A new framework called Rigid Depth Constructor (RDC) is proposed, allowing a user to create his own dataset for the validation of depth map...
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Lob-based deep learning models for stock price trend prediction: a benchmark study
The recent advancements in Deep Learning (DL) research have notably influenced the finance sector. We examine the robustness and generalizability of...
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CH-Bench: a user-oriented benchmark for systems for efficient distant reading (design, performance, and insights)
Data science deals with the discovery of information from large volumes of data. The data studied by scientists in the humanities include large...
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Lower Bounds of Functions on Finite Abelian Groups
The problem of computing the optimum of functions on finite abelian groups is an important problem in mathematics and computer science. Many...
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BARS: a benchmark for airport runway segmentation
Airport runway segmentation can effectively reduce the accident rate during the landing phase, which has the largest risk of flight accidents. With...
