Editorial Board
Metaheuristic-based possibilistic fuzzy k-modes algorithms for categorical data clustering
Ensemble learning from model based trees with application to differential price sensitivity assessment
Edge computing and its role in Industrial Internet: Methodologies, applications, and future directions
An intelligent scheme for big data recovery in Internet of Things based on Multi-Attribute assistance and Extremely randomized trees
Optimizing vehicle routing via Stackelberg game framework and distributionally robust equilibrium optimization method
A secure and privacy-preserving protocol for holding double auctions in smart grid
FastForest: Increasing random forest processing speed while maintaining accuracy
Finite-time fuzzy adaptive quantized output feedback control of triangular structural systems
An agglomerative hierarchical clustering algorithm for linear ordinal rankings
A multi-stage hierarchical clustering algorithm based on centroid of tree and cut edge constraint
A Blockchain-based approach for matching desired and real privacy settings of social network users
A switched fuzzy filter approach to H∞ filtering for Takagi-Sugeno fuzzy Markov jump systems with time delay: The continuous-time case
Regional input-to-state stabilization of fuzzy state-delayed discrete-time systems with saturating actuators
Editorial letter special issue “Business Analytics – Emerging Trends and Challenges”
tcc2vec: RFM-informed representation learning on call graphs for churn prediction
Targeting customers for profit: An ensemble learning framework to support marketing decision-making
HOBA: A novel feature engineering methodology for credit card fraud detection with a deep learning architecture
Combining unsupervised and supervised learning in credit card fraud detection
A constrained agglomerative clustering approach for unipartite and bipartite networks with application to credit networks
The weighted average multiexperton
A novel approach for panel data: An ensemble of weighted functional margin SVM models
Efficient top-k high utility itemset mining on massive data
Distance assessment and analysis of high-dimensional samples using variational autoencoders
Multi-label classification with weighted classifier selection and stacked ensemble
