In this paper, we constructed a new type of skewed generalized normal distribution whose density function contains four parameters, which can give the distribution excellent flexibility and provide an accurate model for actual statistical data analysis. Several important properties of the distribution are presented, and the optimal confidence interval for the distribution parameters was constructed. Through simulation experiments, we verified that the confidence interval we constructed has high accuracy and reliability. In addition, the hypothesis testing problem for this distribution, including the analysis of power functions, has also been discussed in detail. The performance of testing methods under various situations is evaluated, and the optimal two-tailed testing method is proposed. The distribution and statistical analysis methods presented in this article can greatly improve the quality of data analysis.

In this paper, we enhanced change point detection in skew normal distribution models by integrating the EM algorithm's Q-function with the modified information criterion (MIC). The new QMIC framework improves sensitivity and accuracy in detecting changes, outperforming the modified information criterion (MIC) and the traditional Bayesian information criterion (BIC). Due to the complexity of deriving analytic asymptotic distributions, bootstrap simulations were used to determine critical values at various significance levels. Extensive simulations demonstrate that QMIC offers superior detection capabilities. We applied the QMIC method to two stock market datasets, successfully identifying multiple change points, and highlighting its effectiveness for real-world financial data analysis.

To illustrate data uncertainty, intuitionistic fuzzy sets simply use membership and non-membership degrees. However, in some cases, a more complex strategy is required to deal with imprecise data. One of these techniques is generalized intuitionistic fuzzy sets (GIFSs), which provide a comprehensive framework by adding extra factors that provide a more realistic explanation for uncertainty. GIFSs contain generalized membership, non-membership, and hesitation degrees for establishing symmetry around a reference point. In this paper, we applied a generalized intuitionistic fuzzy set approach to investigate ambiguity in the parameter of the Lomax life distribution, seeking a more symmetric assessment of the reliability measurements. Several reliability measurements and associated cut sets for a novel L-R type fuzzy sets are derived after establishing the scale parameter as a generalized intuitionistic fuzzy number. Additionally, the study includes a range of reliability measurements, such as odds, hazards, reliability functions, etc., that are designed for the Lomax distribution within the framework of generalized intuitionistic fuzzy sets. These reliability measurements are an essential tool for evaluating the reliability characteristics of various types of complex systems. For the purpose of interpretation and application, the results are visually displayed and compared across different cut set values using a numerical example.

The research of this topic is based on financial risk control, and Sunshine Jinke's risk prevention and control is taken as a specific research case. The data set uses user consumption data used by Sunshine Jinke. The data source is a bank's customer consumer loan records in the past five years. The feature fields are extracted according to the degree of correlation between the data and the repayment rate, and combined with the convolutional neural network and the recurrent neural network, these feature fields are processed for the differentiation of credit data and fraud data, and finally matched with user information and scored, matching The process uses the singular matrix factorization idea. Through experimental papers, this idea has good stability and accuracy in the field of risk control forecasting.

身份认证是物联网安全可信的第一道防线,是保障感知网络稳定运行的基石.基于感知节点的安全性需求及有限的计算能力,提出一种基于椭圆曲线的双向身份认证协议.该方案能够认证通信感知节点双方身份的真实性,加解密所需密钥信息量少,且不存在密钥协商问题.为解决认证延迟和能量消耗问题,实现簇头节点对同一群组内感知节点的批身份认证,对可疑节点基于二分搜索技术实现身份追踪,快速定位可疑节点位置,及时甄别不可信节点.安全性分析表明,该机制具有正确性、匿名性、不可抵抗性,可有效阻止恶意节点窃取及篡改感知数据.