Search
Search Results
-
Vibration-Based Damage Detection of Arch Dams Using Least-Square Support Vector Machines and Salp Swarm Algorithms
This paper presents a vibration-based damage-detection approach for arch dams using least-square support vector machines and salp swarm algorithms...
-
The implementation of a least square support vector regression model utilizing meta-heuristic algorithms for predicting undrained shear strength
The undrained shear strength (USS) of soil is widely regarded as a crucial parameter in various structural engineering applications, including the...
-
Clusters of floor locations-allocation of stores to cross-docking warehouse considering satisfaction and space using MOGWO and NSGA-II algorithms
Optimal warehouse design is the most substantial issue for many companies, because of increasing their efficiency and productivity. Nowadays, a...
-
Interval prediction of landslide displacement with dual-output least squares support vector machine and particle swarm optimization algorithms
For landslide displacement, interval predictions are generally more realistic and reliable compared with traditional point predictions. This paper...
-
GMO: geometric mean optimizer for solving engineering problems
This paper introduces a new meta-heuristic technique, named geometric mean optimizer (GMO) that emulates the unique properties of the geometric mean...
-
An Augmented Space Smoothing Method based on the Signal Space in Coherent Scenarios
In the field of coherent direction of arrival (DOA) estimation, traditional subspace-based algorithms encounter difficulties due to the loss of rank...
-
Prediction of pile-bearing capacity using Least Square Support Vector Regression: individual and hybrid models development
The primary determinant in pile foundation design is the pile-bearing capacity (PBC), which relies on various soil characteristics and multiple...
-
Machine Learning Regression Algorithms for Shear Strength Prediction of SFRC-DBs: Performance Evaluation and Comparisons
The objective of this study is to assess the shear strength of Deep Steel Fiber Reinforced Concrete Beams without stirrups (SFRC-DBs) and to forecast...
-
Adaptive Sparse Quantization Kernel Least Mean Square Algorithm for Online Prediction of Chaotic Time Series
Kernel least mean square (KLMS) algorithm is a popular method for time series online prediction. It has the advantages of good robustness, low...
-
Optimizing Patient Stratification in Healthcare: A Comparative Analysis of Clustering Algorithms for EHR Data
Advanced data analytics are increasingly being employed in healthcare research to improve patient classification and personalize medicinal therapies....
-
Performance assessment of Kriging with partial least squares for high-dimensional uncertainty and sensitivity analysis
This paper aims to assess the potential of Kriging combined with partial least squares (KPLS) for fast uncertainty quantification and sensitivity...
-
A critical take on the role of random and local search-oriented components of modern computational intelligence-based optimization algorithms
The concept of computational intelligence (CI)-based optimization algorithms emerged in the early 1960s as a more practical approach to the...
-
A Robust Constrained Total Least Squares Algorithm for Three-Dimensional Target Localization with Hybrid TDOA–AOA Measurements
Three-dimensional (3D) target localization by using hybrid time difference of arrival (TDOA) and angle of arrival (AOA) measurements from multiple...
-
Compressive strength prediction of high-performance concrete with utilization of automated least square support vector regression-based algorithm
High-performance concrete (HPC) is extensively employed in the construction sector owing to its exceptional strength and durability. The mechanical...
-
Alternate Least Square and Root Polynomial Based Colour-Correction Method for High Dimensional Environment
The colours of a digital image rely not only on lighting conditions and the features of the capturing device but also on the surface qualities of the...
-
Predicting Compressive Strength of Color Pigment Incorporated Roller Compacted Concrete via Machine Learning Algorithms: A Comparative Study
Due to its low albedo, traditional asphalt pavement contributes to the urban heat island effect. Color pigment added roller compacted high...
-
Outlier Detection Algorithms Over Fuzzy Data with Weighted Least Squares
In the classical leave-one-out procedure for outlier detection in regression analysis, we exclude an observation and then construct a model on the...
-
A general framework for improving cuckoo search algorithms with resource allocation and re-initialization
Cuckoo search (CS) has currently become one of the most favorable meta-heuristic algorithms (MHAs). In this article, a simple yet effective framework...
-
Improved Adaptive Beamforming Algorithms for Wireless Systems
The classical least mean square (LMS) algorithm is a widely studied method for adaptive beamforming. It is well known for its lower computational...
-
Short-Term Load Forecasting Using Machine Learning Algorithms
In meeting the ever-increasing demand for power, electric power distributors must be well-equipped with a prediction mechanism that can accurately...