Search Results - (( variable extracting factor algorithm ) OR ( java application bees algorithm ))
Search alternatives:
- variable extracting »
- factor algorithm »
- java application »
- application bees »
- bees algorithm »
-
1
Development Of Fall Risk Clustering Algorithm In Older People
Published 2020“…A total of 1279 subjects and 9 variables from dataset (1411 subjects and 139 variables) are selected for clustering. t-Distributed Stochastic Neighbour Embedding (t-SNE) for feature extraction and K-means clustering algorithm achieved the highest performance in clustering, which grouping the subjects into Low (13%), Intermediate A (19%), Intermediate B (21%) and High (31%) fall risk group. …”
Get full text
Get full text
Final Year Project / Dissertation / Thesis -
2
Development of an effective clustering algorithm for older fallers
Published 2022“…Using feature extraction with the t-SNE and the K-means clustering algorithm, subjects were clustered into low, intermediate A, intermediate B and high fall risk groups which corresponded with fall occurrence of 13%, 19%, 21% and 31% respectively. …”
Get full text
Get full text
Article -
3
Design of intelligent Qira’at identification algorithm
Published 2017“…Sequential Windowing Parameterizing of Affine Projection Algorithm (SPAP) is proposed to improve windowing parameterizing during echo cancellation, while recognition accuracy factors are taken into account for further improvement. …”
Get full text
Get full text
Thesis -
4
Edge detection and contour segmentation for fruit classification in natural environment / Khairul Adilah Ahmad
Published 2018“…This reserarch adapted a methodology of computer vision and algorithms that exploit image segmentation, feature extraction and fuzzy classification to guide the research activities. …”
Get full text
Get full text
Thesis -
5
HEP-2 CELL IMAGES CLASSIFICATION BASED ON STATISTICAL TEXTURE ANALYSIS AND FUZZY LOGIC
Published 2014“…This project proposes a pattern recognition algorithm consisting of statistical methods to extract seven textural features from the HEp-2 cell images followed by classification of staining patterns by using fuzzy logic. …”
Get full text
Get full text
Final Year Project -
6
HEp-2 cell images classification based on statistical texture analysis and fuzzy logic
Published 2014“…This paper proposes a pattern recognition algorithm consisting of statistical methods to extract seven textural features from the HEp-2 cell images followed by classification of staining patterns by using fuzzy logic. …”
Get full text
Get full text
Conference or Workshop Item -
7
Long-term electrical energy consumption: Formulating and forecasting via optimized gene expression programming / Seyed Hamidreza Aghay Kaboli
Published 2018“…In the developed feature selection approach, multi-objective binary-valued backtracking search algorithm (MOBBSA) is used as an efficient evolutionary search algorithm to search within different combinations of input variables and selects the non-dominated feature subsets, which minimize simultaneously both the estimation error and the number of features. …”
Get full text
Get full text
Get full text
Thesis -
8
Analysis of Traffic Accident Patterns Using Association Rule Mining
Published 2024“…This study also demonstrated the practicality of the apriori algorithm in analyzing extensive datasets to extract actionable insights. …”
Get full text
Get full text
Get full text
Get full text
Article -
9
Short-term electricity price forecasting in deregulated electricity market based on enhanced artificial intelligence techniques / Alireza Pourdaryaei
Published 2020“…A multi-objective feature technique is developed in this study to extract the most influential subsets of input variables with the maximum relevancy and minimum redundancy. …”
Get full text
Get full text
Get full text
Thesis -
10
Classification of students' performance in computer programming course according to learning style
Published 2024Conference Paper -
11
Towards enhanced remaining useful life prediction of lithium-ion batteries with uncertainty using optimized deep learning algorithm
Published 2025“…However, existing RUL prediction approaches have difficulties with variability and nonlinearity that occur during battery degradation, data extraction, feature extraction, hyperparameters optimization, and prediction model uncertainty. …”
Article -
12
-
13
Classification of Students' Performance in Computer Programming Course According to Learning Style
Published 2024“…The critical point of this study is the use of classification algorithm to extract patterns which are examined from the cognitive factor specific learning style. …”
Proceedings Paper -
14
CAT CHAOTIC GENETIC ALGORITHM BASED TECHNIQUE AND HARDWARE PROTOTYPE FOR SHORT TERM ELECTRICAL LOAD FORECASTING
Published 2017“…In this research work, a modified backpropagation neural network is combined with a modified chaos-search genetic algorithm for STLF of one day and a week ahead. Multiple modifications are carried out on the conventional back-propagation (BP) algorithm such as, improvements in the momentum factor and adaptive learning rate. …”
Get full text
Get full text
Thesis -
15
The Role of Sustainable Competitiveness Indicator in Malaysian Tourism and Economic Growth
Published 2024“…The resultant indicator is consisted of 12 variables, identified based on the pillars of sustainability and competitiveness to extract a common vulnerability component using a dynamic approximate factor model. …”
Get full text
Get full text
Get full text
Get full text
Article -
16
-
17
Development of a phantom and metal artifact correction (MAC) algorithm for post-operative spine computed tomography (CT) imaging / Noor Diyana Osman
Published 2014“…There are 3 different variables studied which were metal insert characteristics, exposure factors, and reconstruction parameters. …”
Get full text
Get full text
Thesis -
18
A novel ensemble decision tree-based CHi-squared Automatic Interaction Detection (CHAID) and multivariate logistic regression models in landslide susceptibility mapping
Published 2014“…CHAID as a multivariate method has an automatic classification capacity to analyze large numbers of landslide conditioning factors. Moreover, it results two or more nodes for each independent variable, where every node contains numbers of presence or absence of landslides (dependent variable). …”
Get full text
Get full text
Article -
19
High-Resolution Downscaling with Interpretable Relevant Vector Machine: Rainfall Prediction for Case Study in Selangor
Published 2024“…While machine learning eliminates the requirement for manual feature selection when extracting significant information from predictor fields, considering multiple pivotal factors is essential. …”
Get full text
Get full text
Article -
20
Clinical relevance of VKORC1 (G-1639A and C1173T) and CYP2C9*3 among patients on warfarin
Published 2011“…Other important influential factors affecting warfarin dose requirement remain to be identified.…”
Get full text
Get full text
Article
