Table 1 List of abbreviations

From: Machine learning methods for predicting residual strength in corroded oil and gas steel pipes

Terminology

Abbreviation

Terminology

Abbreviation

Adaptive Neuro Fuzzy Inference System

ANFIS

K Nearest Neighbor

KNN

Artificial Neural Networks

ANN

Kernel Principal Component Analysis

KPCA

Back Propagation Neural Network

BPNN

Locally Linear Embedding

LLE

Bayesian Regularized Artificial Neural Network

BRANN

Mean Absolute Error

MAE

Cuckoo Search

CS

Mean Absolute Percentage Error

MAPE

Deep Extreme Learning Machine

DELM

Multilayer Perceptron

MLP

Decision Tree

DT

Multiple Objective Grey Wolf Optimizer

MOGWO

Extreme Learning Machines

ELM

Multiple Objective Sparrow Search Algorithm

MOSSA

Finite Element Analysis

FEA

Mean Squared Error

MSE

Finite Element Method

FEM

Non-dominated Sorting Genetic Algorithms

NSGA

Feedforward Neural Network

FFNN

Principal Component Analysis

PCA

Fruit Fly Optimization Algorithm

FOA

Particle Swarm Optimization

PSO

Genetic Algorithm

GA

Radial Basis Function Neural Network

RBFNN

Generalized Additive Model

GAM

Random Forest

RF

Generative Adversarial Networks

GAN

Root Mean Square Error

RMSE

Gradient Boosting Decision Tree

GBDT

Relevance Vector Machine

RVM

Gradient Boosting Machines

GBM

Subspace Clustered Neural Network

SSCN

Genetic Programming

GP

Support Vector Machines

SVM

Gaussian Process Regression

GPR

Support Vector Regression

SVR

General Regression Neural Network

GRNN

Teaching-Learning-Based Optimization

TLBO

Hybrid Teaching-Learning-Based Optimization

HTLBO

Tree-structured Parzen Estimator

TPE

Improved Particle Swarm Optimization

IPSO

Whale Optimization Algorithm

WOA

Isometric Feature Mapping

ISOMAP

eXtreme Gradient Boosting

XGBoost

Extra Trees Regressor

ETR

Synthetic Minority Oversampling Technique

SMOTE

Shapley Additive Explanations

SHAP

Local Interpretable Model-agnostic Explanations

LIME