Results 41 to 50 of about 917,720 (266)
In order to solve the problem of selecting frequency more and more difficultly for radio network,an intelligent frequency selection technology based on an adaptive genetic algorithm was proposed.Frequencies were selected for whole radio network from the ...
Wenjun Wang
doaj +2 more sources
A new genetic algorithm for multi-label correlation-based feature selection. [PDF]
This paper proposes a new Genetic Algorithm for Multi-Label Correlation-Based Feature Selection (GA-ML-CFS). This GA performs a global search in the space of candidate feature subset, in order to select a high-quality feature subset is used by a multi ...
Freitas, Alex A., Jungjit, Suwimol
core
In this study, we compared three methods for kinship identification using different algorithms in samples of wild Pacific bluefin tuna and generated genotyping data. The three methods resulted in different numbers of inferred kinship pairs for both generated and actual data. Particularly for the half‐sibling pairs, considerable number of false‐positive
Yohei Tsukahara+5 more
wiley +1 more source
Hermansky‐Pudlak syndrome type 1 (HPS‐1) is a rare, autosomal recessive disorder with poorly understood renal involvement. Urinary extracellular vesicle (uEV) proteomics and a novel Hps1 mouse model reveal mitochondrial abnormalities and lipid accumulation in HPS‐1 kidney proximal tubule cells. Serum ApoA1 correlates with kidney function in our patient
Dawn M. Maynard+7 more
wiley +1 more source
Protection Strategy Selection Model Based on Genetic Ant Colony Optimization Algorithm
Industrial control systems (ICS) are facing an increasing number of sophisticated and damaging multi-step attacks. The complexity of multi-step attacks makes it difficult for security protection personnel to effectively determine the target attack path ...
Xinzhan Li+4 more
doaj +1 more source
Genetic optimization algorithms applied toward mission computability models [PDF]
Genetic algorithms are modeled after the biological evolutionary processes that use natural selection to select the best species to survive. They are heuristics based and low cost to compute. Genetic algorithms use selection, crossover, and mutation to obtain a feasible solution to computational problems.
arxiv
Anisotropic selection in cellular genetic algorithms [PDF]
In this paper we introduce a new selection scheme in cellular genetic algorithms (cGAs). Anisotropic Selection (AS) promotes diversity and allows accurate control of the selective pressure. First we compare this new scheme with the classical rectangular grid shapes solution according to the selective pressure: we can obtain the same takeover time with ...
arxiv +1 more source
Comparison of a Greedy Selection Operator to Tournament Selection and a Hill Climber [PDF]
A new deterministic greedy genetic algorithm selection operator with very high selection pressure, dubbed the Jugate Adaptive Method is examined.
Borbone, John, Graham, Lee, Parker, Gary
core +2 more sources
We describe a novel set of Epac‐based FRET‐FLIM biosensors with improved fully cytosolic distribution, achieved without compromising the state‐of‐the‐art performance of our original designs, for detecting cAMP dynamics in real time in live cells with high precision and reliability.
Giulia Zanetti+2 more
wiley +1 more source
Self-Tune Linear Adaptive-Genetic Algorithm for Feature Selection
Genetic algorithm (GA) is an established machine learning technique used for heuristic optimisation purposes. However, this natural selection-based technique is prone to premature convergence, especially of the local optimum event.
Ching Sheng Ooi+2 more
doaj +1 more source