Search Results - (( data selection methods algorithm ) OR ( variable generation based algorithm ))
Search alternatives:
- variable generation »
- selection methods »
- methods algorithm »
- generation based »
- data selection »
-
1
Artificial immune system based on real valued negative selection algorithms for anomaly detection
Published 2015“…The Real-Valued Negative Selection Algorithms, which are the focal point of this research, generate their detector sets based on the points of self data. …”
Get full text
Get full text
Get full text
Get full text
Thesis -
2
Efficient genetic partitioning-around-medoid algorithm for clustering
Published 2019“…However, the complexity of the kmedoid based algorithms in general is more than the complexity of the k-means based algorithms. …”
Get full text
Get full text
Thesis -
3
Optimization and control of hydro generation scheduling using hybrid firefly algorithm and particle swarm optimization techniques
Published 2018“…To deal with these problems, this thesis introduces three approved intelligent controllers for hydropower generation. Firstly, a hybrid algorithm namely firefly particle swarm optimization (FPSO) and series division method (SDM) based on the practical swarm optimization and the firefly algorithm is proposed. …”
Get full text
Get full text
Thesis -
4
Variable Neighbourhood Search Algorithm for Vehicle Routing Problem with Backhaul
Published 2023“…Thus, a heuristic approach based on the Variable Neighbourhood Search (VNS) is proposed. …”
Get full text
Get full text
Get full text
Get full text
Thesis -
5
Improvement of land cover mapping using Sentinel 2 and Landsat 8 imageries via non-parametric classification
Published 2020“…The last phase involves developing a new fusion algorithm using SVM and Fuzzy K-Means Clustering (FKM) algorithms for Sentinel 2 data to enhance LCM accuracy. …”
Get full text
Get full text
Thesis -
6
Improvement on rooftop classification of worldview-3 imagery using object-based image analysis
Published 2019“…Furthermore, a systematic feature selection approach was proposed in which search algorithms (Ant-Search, Best First-Search and Particle Swamp Optimization (PSO) - Search) performance were evaluated to select the most significant features. …”
Get full text
Get full text
Thesis -
7
Edge detection and contour segmentation for fruit classification in natural environment / Khairul Adilah Ahmad
Published 2018“…This learning algorithm represents an automatic generation of membership functions and rules from the data. …”
Get full text
Get full text
Thesis -
8
Variable Neighborhood Descent and Whale Optimization Algorithm for Examination Timetabling Problems at Universiti Malaysia Sarawak
Published 2025“…The model employs a two-level structure, where the first level uses standard soft constraints as the objective function to evaluate solution quality, while the second level dynamically adapts to faculty-specific preferences. A constructive algorithm was developed to generate an initial feasible solution, which was subsequently refined using two primary approaches to evaluate their efficiency: Iterative Threshold Pipe Variable Neighborhood Descent (IT-PVND), and a modified Whale Optimization Algorithm (WOA). …”
Get full text
Get full text
Get full text
Get full text
Thesis -
9
Fault detection and diagnosis using correlation coefficients
Published 2005“…This research is to formulate a FDD algorithm based on MSPC via correlation coefficients. …”
Get full text
Get full text
Thesis -
10
Determining malaria risk factors in Abuja, Nigeria using various statistical approaches
Published 2018“…Therefore, this was not incorporated in BBN models. Based on cross-validation analysis, the score-based algorithm outperformed the constraint-based algorithms in the structural learning. …”
Get full text
Get full text
Thesis -
11
Evaluation of lightning return stroke current using measured electromagnetic fields
Published 2012“…However, the improvement of Deindorfer and Uman on the Heidler function with an unknown variable is selected as the general channel base current function. …”
Get full text
Get full text
Thesis -
12
-
13
-
14
Predictive Framework for Imbalance Dataset
Published 2012“…This research was conducted based on limited number of datasets, test sets and variables. …”
Get full text
Get full text
Get full text
Get full text
Thesis -
15
Development of robust procedures for partial least square regression with application to near infrared spectral data
Published 2021“…To fill-in the gap in the literature, a new robust procedure in wavelength selection based on input scaling method is developed using Filter-Wrapper method. …”
Get full text
Get full text
Thesis -
16
High-Resolution Downscaling with Interpretable Relevant Vector Machine: Rainfall Prediction for Case Study in Selangor
Published 2024“…The Principal Component Analysis (PCA) technique was employed to choose relevant environmental variables as input for the machine learning model, and various imputation methods were utilized to manage missing data, such as mean imputation and the KNN algorithm. …”
Get full text
Get full text
Article -
17
Developing an ensembled machine learning prediction model for marine fish and aquaculture production
Published 2023“…The past 20 years (2000�2019) of climatic variables and fish production data were used to train and test the ML models. …”
Article -
18
Investigation of fault detection and isolation accuracy of different Machine learning techniques with different data processing methods for gas turbine
Published 2022“…Faulty and non-faulty data were generated from the developed performance model. Based on sensitivity analysis, 12 measurement parameters and 11,824 data points were selected for the development of a fault detection and isolation model. …”
Get full text
Get full text
Article -
19
Investigation of fault detection and isolation accuracy of different Machine learning techniques with different data processing methods for gas turbine
Published 2022“…Faulty and non-faulty data were generated from the developed performance model. Based on sensitivity analysis, 12 measurement parameters and 11,824 data points were selected for the development of a fault detection and isolation model. …”
Get full text
Get full text
Article -
20
What, how and when to use knowledge in neural network application
Published 2004“…The methodology comprises five steps namely variable selection, data collection, data preprocessing, training &validation, and testing.…”
Get full text
Get full text
Conference or Workshop Item