The non-excavation corrosion prediction model of grounding grid based on particle swarm optimization extreme learning machine
نویسندگان
چکیده
منابع مشابه
S3PSO: Students’ Performance Prediction Based on Particle Swarm Optimization
Nowadays, new methods are required to take advantage of the rich and extensive gold mine of data given the vast content of data particularly created by educational systems. Data mining algorithms have been used in educational systems especially e-learning systems due to the broad usage of these systems. Providing a model to predict final student results in educational course is a reason for usi...
متن کاملMedical Dataset Classification: A Machine Learning Paradigm Integrating Particle Swarm Optimization with Extreme Learning Machine Classifier
Medical data classification is a prime data mining problem being discussed about for a decade that has attracted several researchers around the world. Most classifiers are designed so as to learn from the data itself using a training process, because complete expert knowledge to determine classifier parameters is impracticable. This paper proposes a hybrid methodology based on machine learning ...
متن کاملFault Diagnosis of Power Transformers using Kernel based Extreme Learning Machine with Particle Swarm Optimization
To improve the fault diagnosis accuracy for power transformers, this paper presents a kernel based extreme learning machine (KELM) with particle swarm optimization (PSO). The parameters of KELM are optimized by using PSO, and then the optimized KELM is implemented for fault classification of power transformers. To verify its effectiveness, the proposed method was tested on nine benchmark classi...
متن کاملParameters Selection of Kernel Based Extreme Learning Machine Using Particle Swarm Optimization
The generalization performance of kernel based extreme learning machine (KELM) with Gaussian kernel are sensitive to the parameters combination (C, γ). The best generalization performance of KELM with Gaussian kernel is usually achieved in a very narrow range of such combinations. In order to achieve optimal generalization performance, the parameters of KELM with Gaussian kernel were optimized ...
متن کاملThe application of Committee machine with particle swarm optimization to the assessment of permeability based on thin section image analysis
Permeability is the ability of porous rock to transmit fluids and one of the most important properties of reservoir rock because oil production depends on the permeability of reservoirs. Permeability is determined using a variety of methods which are usually expensive and time consuming. Reservoir rock properties with image analysis and intelligent systems has been used to reduce time and money...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: IOP Conference Series: Earth and Environmental Science
سال: 2021
ISSN: 1755-1307,1755-1315
DOI: 10.1088/1755-1315/692/2/022118