2 research outputs found
Modeling the Telemarketing Process using Genetic Algorithms and Extreme Boosting: Feature Selection and Cost-Sensitive Analytical Approach
Currently, almost all direct marketing activities take place virtually rather
than in person, weakening interpersonal skills at an alarming pace.
Furthermore, businesses have been striving to sense and foster the tendency of
their clients to accept a marketing offer. The digital transformation and the
increased virtual presence forced firms to seek novel marketing research
approaches. This research aims at leveraging the power of telemarketing data in
modeling the willingness of clients to make a term deposit and finding the most
significant characteristics of the clients. Real-world data from a Portuguese
bank and national socio-economic metrics are used to model the telemarketing
decision-making process. This research makes two key contributions. First,
propose a novel genetic algorithm-based classifier to select the best
discriminating features and tune classifier parameters simultaneously. Second,
build an explainable prediction model. The best-generated classification models
were intensively validated using 50 times repeated 10-fold stratified
cross-validation and the selected features have been analyzed. The models
significantly outperform the related works in terms of class of interest
accuracy, they attained an average of 89.07\% and 0.059 in terms of geometric
mean and type I error respectively. The model is expected to maximize the
potential profit margin at the least possible cost and provide more insights to
support marketing decision-making
Protecting Digital Images Using Keys Enhanced by 2D Chaotic Logistic Maps
This research paper presents a novel digital color image encryption approach that ensures high-level security while remaining simple and efficient. The proposed method utilizes a composite key r and x of 128-bits to create a small in-dimension private key (a chaotic map), which is then resized to match the color matrix dimension. The proposed method is uncomplicated and can be applied to any image without any modification. Image quality, sensitivity analysis, security analysis, correlation analysis, quality analysis, speed analysis, and attack robustness analysis are conducted to prove the efficiency and security aspects of the proposed method. The speed analysis shows that the proposed method improves the performance of image cryptography by minimizing encryption–decryption time and maximizing the throughput of the process of color cryptography. The results demonstrate that the proposed method provides better throughput than existing methods. Overall, this research paper provides a new approach to digital color image encryption that is highly secure, efficient, and applicable to various images