Kongzhi yu Juece/Control and Decision

Optimizing Failure Prediction in Cloud Computing Using LSTM and MLP Integration

Accurate failure prediction in cloud computing is vital for maintaining system reliability and minimizing downtime. This paper presents an optimized approach for cloud failure prediction by integrating Long Short-Term Memory (LSTM) and Multi-Layer Perceptron (MLP) models, leveraging the Google Cloud Trace dataset. To enhance the predictive accuracy and efficiency of the models, Grey Wolf Optimization (GWO) algorithm is employed for feature selection, ensuring that the most relevant features are utilized in the prediction process. The integration of LSTM's temporal sequence learning capabilitie

The exploration and practice for the cultivation of the thinking ability of "data-based decision making" in teaching reform of chemical thermodynamics

The exploration and practice for the cultivation of the thinking ability of "data-based decision making" in teaching reform of chemical thermodynamicsThe exploration and practice for the cultivation of the thinking ability of "data-based decision making" in teaching reform of chemical thermodynamicsThe exploration and practice for the cultivation of the thinking ability of "data-based decision making" in teaching reform of chemical thermodynamicsThe exploration and practice for the cultivation of the thinking ability of "data-based decision making" in

Prediction of Ventilator Breathing Parameters on an Automated Ventilation System using Regression Models

Medical staff face issues when ventilating patients manually using the Bag-Valve-Mask (BVM) for long periods. As for ventilators in hospitals, medical specialists must check on patients frequently and adjust settings manually. This study aims to conduct machine learning (ML) study using data collected from the CHU Sainte-Justine database to provide suitable setting recommendations for patients using linear and Poisson regression. The response variables were the fraction of inspired oxygen (FiO2) setting, positive end-expiratory pressure (PEEP) setting and tidal volume (TV) setting. Linear regr

A STUDY ON IMPACT OF CORPOTATE TAX FRAUD ON ECNOMIC GROWTH AND FACTORS INFLUENSING THE TAX COMPLIANCE.

This paper aims to identify the impact of corporate tax fraud on Economic growth and the factors influencing the tax compliance. A sample of 258 auditors has been taken for the study. Samples were selected as per convenience sampling method. Chi square test and Proportional test has been used to analyses the data. The analysis reveals that corporate tax fraud seriously effecting the economic growth of a country. The analysis also done to find out the top factors effecting the tax compliance.

The Solution of the -Dimensional of the Operator D_{B,C}^k

In this paper,  the operator $D_{B,C}^k$ is the partial differential operators related to the diamond Bessel operator  iterated $k$-times and is defined by $$D_{B,C}^{k}= \left(\frac{1}{C^4}\left(\sum_{i=1}^{p} B_{x_i}\right)^2- \left( \sum_{j=p+1}^{p+q} B_{x_j}\right)^2 \right)^k,$$ 

where $p+q=n, x=(x_{1},\ldots , x_{n})\in \mathbb{R}^{+}_n, B_{x_{i}}=\frac{\partial ^{2}}{\partial x_{i}^{2}}+ \frac{2v_{i}In this paper, the operator is the partial differential operators related to the diamond Bessel operator iterated -times and is defined by where , , is a