A supervised machine learning method, the support vector machine (SVM) algorithm [ 1], has demonstrated high performance in solving classification problems in many biomedical fields, especially in bioinformatics [ 2, 3].
Massive datasets in emerging fields such as geosciences, biology, and networking do require parallel and distributed computations with high performance to solve real-world problems.
Startups have capitalized on that by creating high performance, scalable integrations, solving hard technical problems like how to sync without putting excessive load on the underlying system.
A dense mesh requires high performance algorithms for solving the direct and inverse problems.
A simple but costly solution would be the use of high performance computers to solve the complex problems.
Use of the harmony search (HS) as a high performance algorithm to solve the formulated discrete optimization problem, without the need for any clustering method.
4) Use of the harmony search (HS) as a high performance algorithm to solve the formulated discrete optimization problem, without the need for any clustering method.
Because of high needed computational time, we utilized a high performance computer and solved a real instance from a dataset introduced by wen et al. (Wen et al. 2009) with 40 nodes including 20 suppliers and 20 customers with one cross-dock.
Yeti, a small manufacturer of high performance racing bikes, solved the problem of suspension bicycles.
The same APSO-MST algorithm was adopted to minimize wake effect and cable cost of the OWF, due to high performance of PSO to solve such continuous problems (finding the optimal locations).
