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Issue title: Special Section: Intelligent Data Aggregation Inspired Paradigm and Approaches in IoT Applications
Guest editors: Xiaohui Yuan and Mohamed Elhoseny
Article type: Research Article
Authors: Luo, T.a; * | Metawa, Nourab; c
Affiliations: [a] School of Economics, Xihua University, Chengdu, China | [b] Anderson College of Business, Regis University, USA | [c] Faculty of Commerce, Mansoura University, Egypt
Correspondence: [*] Corresponding author. T. Luo, School of Economics, Xihua University, Chengdu, China. E-mail: taoman22440199@126.com.
Abstract: Financial mathematics, an interdisciplinary subject between mathematics and finance, is the application of mathematics in the financial field, which carries mainly out the quantitative analysis and research of financial issues by mathematical theories and methods. The idea of financial mathematics is adopted to study investment. First of all, an investment risk prediction model is designed based on cluster analysis-hybrid genetic algorithm and integrated improved support vector machine, and AdaBoost-support vector machine and clustering-AdaBoost support vector machine, the model is fully analyzed and verified. Combining the ways of more than half random sampling, the imbalance state is adjusted and reduced. Then the idea of integrated learning is used to cope further the data imbalance state and improve the classifier’s attention to a few classes. Finally, the algorithm is tested. The results show that this algorithm effectively reduces the cost of accidentalinjury.
Keywords: stochastic interest rate, stochastic volatility, optimal investment, reinsurance
DOI: 10.3233/JIFS-179085
Journal: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 1, pp. 283-292, 2019
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