Search
Search Results
-
Deep Neural-Fuzzy System Algorithms with Improved Interpretability for Classification Problems
The adaptive neuro-fuzzy inference system (ANFIS), an efficient soft computing approach, has both high interpretability and self-learning ability....
-
An ensemble algorithm using quantum evolutionary optimization of weighted type-II fuzzy system and staged Pegasos Quantum Support Vector Classifier with multi-criteria decision making system for diagnosis and grading of breast cancer
Breast cancer is a life-threatening and consequential disease due to its invasive and proliferative trait, predominantly found in women. Early...
-
HFS-based computational method for weighted fuzzy time series forecasting model using techniques of adaptive radius clustering and grey wolf optimization
Recently, hesitant fuzzy sets (HFSs) have been used extensively in time series forecasting. HFSs have inherent characteristics of addressing problem...
-
A multi-level consensus function clustering ensemble
In order to improve the performance of a clustering on a data set, a number of primary partitions are generated and stored in an ensemble and their...
-
Tourism demand forecasting using stacking ensemble model with adaptive fuzzy combiner
Over the last decades, several soft computing techniques have been applied to tourism demand forecasting. Among these techniques, a neuro-fuzzy model...
-
Design of Ensemble Fuzzy-RBF Neural Networks Based on Feature Extraction and Multi-feature Fusion for GIS Partial Discharge Recognition and Classification
A new topology of ensemble fuzzy-radial basis function neural networks (EFRBFNN) based on a multi-feature fusion strategy is proposed to recognize...
-
A novel Fuzzy TOPSIS based hybrid jarratt butterfly optimization for optimal routing and cluster head selection in WSN
Wireless Sensor Networks (WSNs) are considered a a develo** versatile as well as low-cost solution that enables wireless communication as well as...
-
Ensemble Learning
This chapter is concerned with the ensemble learning as an alternative advanced learning to the deep learning. It refers to the learning type for...
-
Long-term prediction of time series based on fuzzy time series and information granulation
Time-series prediction involves forecasting future data by analyzing and modeling historical data. The prediction process involves analyzing and...
-
Retention Prediction in the Gaming Industry: Fuzzy Machine Learning Approach
Traditional machine learning algorithms may not produce satisfactory results on high-dimensional and imbalanced datasets. Therefore, the popularity...
-
An improved ant-based algorithm based on heaps merging and fuzzy c-means for clustering cancer gene expression data
The microarray technology enables the analysis of the gene expression data and the understanding of the important biological processes in an...
-
Clustering of Single-Cell Transcriptome Data Based on Evolutionary Algorithm in Assimilation with Fuzzy C-Means
Single-cell transcriptome sequencing (scRNA-seq) technology enables to analyze the RNA expression of each cell over a different instance of time....
-
A Hybrid Method for Big Data Analysis Using Fuzzy Clustering, Feature Selection and Adaptive Neuro-Fuzzy Inferences System Techniques: Case of Mecca and Medina Hotels in Saudi Arabia
Nowadays, social data analysis is widely used in different businesses. Machine learning has proved its effectiveness in big data analysis for...
-
Adaptive fuzzy deformable fusion and optimized CNN with ensemble classification for automated brain tumor diagnosis
Automatic classification of brain tumor plays a vital role to speed up the treatment procedure, plan and boost the survival rate of patients....
-
Dominant Partitioning of Rock Masses Discontinuities Based on Information Entropy Selective Heterogeneous Ensemble
In order to make up for the shortcomings of traditional discontinuity occurrence clustering algorithms, such as narrow application scope, difficulty...
-
Multimodal Perturbation and Cluster Pruning Based Selective Ensemble Classifier and Its Iron Industrial Application
The selective ensemble aims to search the optimal subset balanced accuracy and diversity from the original base classifier set to construct an...
-
Accurate MRI brain tumor segmentation based on rotating triangular section with fuzzy C- means optimization
This paper proposes an accurate MRI brain tumor segmentation based on a Rotating Triangular Section with Fuzzy C-Means Optimization. Magnetic...
-
Clustering
This chapter provides a comprehensive overview of traditional clustering algorithms, which have been fundamental in the field of unsupervised...
-
Mobile App Usage Pattern Prediction Using Hierarchical Flexi-Ensemble Clustering (HFEC) for Mobile Service Rating
Nowadays, the mobile app market becomes rapidly increased in world wide. The mobile app marketers have smart enough to understand the requirements...
-
A new fuzzy MLE-clustering approach based on object-to-group probabilistic distance measure: from anomaly detection to multi-fault classification in datacenter computational nodes
Datacenters are expanding in size and complexity to the point where anomaly detection and infrastructure monitoring become critical challenges. One...
