Nature-Inspired Optimization Algorithm
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Benchmarks
Most implemented
FlexChunk: Enabling 100M×100M Out-of-Core SpMV (~1.8 min, ~1.7 GB RAM) with Near-Linear Scaling
Finite Element Model Updating Using Fish School Search Optimization Method
Papers
FlexChunk: Enabling 100M×100M Out-of-Core SpMV (~1.8 min, ~1.7 GB RAM) with Near-Linear Scaling
Handling large-scale sparse matrices is a fundamental task in many scientific and engineering domains, yet standard in-memory approaches often hit the limitations of available RAM. This paper introduces FlexChunk, an alg…
ChunkingNature-Inspired Optimization AlgorithmAmélioration de la qualité d'images avec un algorithme d'optimisation inspirée par la nature
Reproducible images preprocessing is important in the field of computer vision, for efficient algorithms comparison or for new images corpus preparation. In this paper, we propose a method to obtain an explicit and order…
Nature-Inspired Optimization AlgorithmPosition-wise optimizer: A nature-inspired optimization algorithm
The human nervous system utilizes synaptic plasticity to solve optimization problems. Previous studies have tried to add the plasticity factor to the training process of artificial neural networks, but most of those mode…
Nature-Inspired Optimization AlgorithmPositionWhy the Firefly Algorithm Works?
Firefly algorithm is a nature-inspired optimization algorithm and there have been significant developments since its appearance about ten years ago. This chapter summarizes the latest developments about the firefly algor…
Nature-Inspired Optimization AlgorithmFinite Element Model Updating Using Fish School Search Optimization Method
A recent nature inspired optimization algorithm, Fish School Search (FSS) is applied to the finite element model (FEM) updating problem. This method is tested on a GARTEUR SM-AG19 aeroplane structure. The results of this…
Nature-Inspired Optimization Algorithm