scholarly journals RANDOM FOREST ALGORITHM OPTIMIZATION OF ENTERPRISE FINANCIAL INFORMATION MANAGEMENT SYSTEM

2018 ◽  
Vol 48 (4) ◽  
pp. 255-260
Author(s):  
X. H. LIU ◽  
E. X. WANG ◽  
Y. Q. ZHENG
Keyword(s):  
Random Forest ◽  
Information Management ◽  
Financial Management ◽  
Management System ◽  
Prediction Method ◽  
Information Management System ◽  
Financial Information ◽  
Random Forest Model ◽  
Random Forest Algorithm ◽  
Forest Model

The optimization of random forest algorithms for enterprise financial information management systems is studied in this paper. A random forest algorithm was proposed to improve the data processing capabilities of the financial system. This paper proposes a random forest model on the premise of referring to the latest results of machine learning. The algorithm was introduced into the real estate business financial management system in this paper. First, the samples are divided into training samples and test samples, and the direct prediction method and the two-step prediction method are applied. Mean SR and MAPE were used to compare the prediction accuracy of different algorithms and it was found that the direct prediction method is better. In the algorithm used in this paper, the random forest effect is the best. Then the linear regression, decision tree, neural network and random forest model fitting effects were compared and the best fitting degree of random forest was found.

Research on Manufacturing Engineering with Financial Information Management System Inter Control in Technology-Based Small and Medium-Sized Enterprises

2014 ◽  
Vol 910 ◽  
pp. 381-384
Author(s):  
Jie Chen
Keyword(s):  
Information System ◽  
Information Management ◽  
Internal Control ◽  
Management System ◽  
Information Management System ◽  
Financial Information ◽  
High Tech ◽  
Main Body ◽  
Science Content ◽  
Manufacturing Engineering

Manufacturing Engineering makes the technical science content high, if enterprise wants to utilize this kind of technical effect well .Small and medium-sized enterprises refers to the scientific and technical personnel as the main body, it is an intelligence intensive economic entity which mainly engaged in high-tech research and development, production of high-tech products and business, independent accounting. The main contents of this paper: The significance of financial information management system inter control; The specific application of financial information system under the environment of ERP; Strategies of improving the internal control of accounting information system.

The Foundation of Campus Card System Platform Construction and Application Function Analysis

2012 ◽  
Vol 457-458 ◽  
pp. 641-643
Author(s):  
Guang Biao Sun ◽  
Jun Zheng ◽  
Hong Wang
Keyword(s):  
Information Management ◽  
Financial Management ◽  
Management System ◽  
Function Analysis ◽  
Information Management System ◽  
Ic Card ◽  
Digital Campus ◽  
Card System ◽  
Bank Card

With the continuous development of digital campus, Card system has become an important content of the digital campus. Campus Card Information Management System is the advanced IC card and network communication technology through the card platform. Campus Card system effectively set bank card financial functions and e-purse, identification and other integrated application features in a campus card. The Campus Car plays a toll bridge in the role of through it with other school information management system modules connected, the entire campus into a data network so that all aspects of campus management, especially financial management to achieve high information Campus one-card "system the author through the campus one-card in the construction of digital campus application, analysis, "card" had a profound effect on college financial management information.

scholarly journals Using The Random Forest Algorithm To Detect The Activity of Thyroid-Associated Ophthalmopathy

2021 ◽  
Author(s):  
Minghui Wang ◽  
Hanqiao Zhang ◽  
Li Dong ◽  
Yang Li ◽  
Zhijia Hou ◽  
...  
Keyword(s):  
Random Forest ◽  
Predictive Value ◽  
Diagnostic Performance ◽  
Operating Characteristic ◽  
Characteristic Curve ◽  
Random Forest Model ◽  
Random Forest Algorithm ◽  
Forest Model ◽  
Thyroid Associated Ophthalmopathy ◽  
Operating Characteristic Curve

Abstract Objective: The aim of this study is to establish a random forest model to detect active and quiescent phases of patients with Thyroid-associated ophthalmopathy (TAO) and to evaluate its diagnostic performance.Methods：A total of 146 patients (292 eyes) who were diagnosed with TAO and were treated in the Ophthalmology Outpatient Clinic of Beijing TongRen hospital were retrospectively included in the study. We took the clinical activity score of TAO as the target; took gender, age, smoking status, I-131 treatment history, thyroid nodules, thyromegaly, thyroid hormone and TSH-receptor antibodies (TRAb) as predictive characteristic variables to establish a random forest model. The proportion of the training group to the testing group was 7:3. We analyzed the model’s accuracy, precision, sensitivity, specificity, positive predictive value (PPV), negative predictive value (PPV), F1 score and out-of-bag (OOB) error, with the accuracy, the brier loss and the area under the receiver operating characteristic curve compared with logistic regression model.Results：Our model has an accuracy of 0.93, a sensitivity of 0.88, a specificity of 0.96, a positive predictive value of 0.94, a negative predictive value of 0.93, an F1 score of 0.91 and an OOB error of 0.12. The accuracy of the random forest model and the logistic regression model were 0.93 and 0.79, respectively, the brier loss were 0.06 and 0.20, and the area under the receiver operating characteristic curve were 0.95 and 0.86.Conclusion：By integrating these high-risk factors, the random forest algorithm can be used as a complementary diagnostic method to determine the activity of TAO, showing prominent diagnostic performance.

scholarly journals A Random Forest Method to Forecast Downbursts Based on Dual-Polarization Radar Signatures

2019 ◽  
Vol 11 (7) ◽  
pp. 826 ◽  
Author(s):  
Bruno Medina ◽  
Lawrence Carey ◽  
Corey Amiot ◽  
Retha Mecikalski ◽  
William Roeder ◽  
...  
Keyword(s):  
Random Forest ◽  
Prediction Method ◽  
The United States ◽  
Random Forest Model ◽  
Dual Polarization ◽  
Forest Model ◽  
Random Forest Method ◽  
Reliable Performance ◽  
Radar Signatures ◽  
Kennedy Space

The United States Air Force’s 45th Weather Squadron provides wind warnings, including those for downbursts, at the Cape Canaveral Air Force Station and Kennedy Space Center (CCAFS/KSC). This study aims to provide a Random Forest model that classifies thunderstorms’ downburst and null events using a 35-knot wind threshold to separate these two categories. The downburst occurrence was assessed using a dense network of wind observations around CCAFS/KSC. Eight dual-polarization radar signatures that are hypothesized to have physical implications for downbursts at the surface were automatically calculated for 209 storms and ingested into the Random Forest model. The Random Forest model predicted null events more correctly than downburst events, with a True Skill Statistic of 0.40. Strong downburst events were better classified than those with weaker wind magnitudes. The most important radar signatures were found to be the maximum vertically integrated ice and the peak reflectivity. The Random Forest model presented a more reliable performance than an automated prediction method based on thresholds of single radar signatures. Based on these results, the Random Forest method is suggested for continued operational development and testing.

Design on Enterprise Information Management System Based on SSH Frame

2012 ◽  
Vol 198-199 ◽  
pp. 233-237
Author(s):  
Ying Xin Liu ◽  
Wei Shi
Keyword(s):  
Information Management ◽  
Financial Management ◽  
Management System ◽  
Information Management System ◽  
Enterprise Management ◽  
Enterprise Information ◽  
Development Platform ◽  
User Management ◽  
Development Framework ◽  
Development Technology

In order to improve the efficiency of enterprise management, the information management system uses Windows XP as the development platform, JSP as development technology and SSH as development framework to realize functions including basic information management, security management, operation management, financial management, item management and user management. The system can be used in different platform and improve operational benefit effectively.

scholarly journals Pendayagunaan Software Asisten Dalam Pengelolaan Sistem Informasi Manajemen Keuangan Sekolah

2020 ◽  
Vol 4 (1) ◽  
pp. 13
Author(s):  
Iqbal Bukhori ◽  
Imas Siti Rojab ◽  
Iwan Sopwandin ◽  
Ara Hidayat
Keyword(s):  
Information Management ◽  
Financial Management ◽  
Management System ◽  
Input Data ◽  
Financial Information ◽  
Financial Data ◽  
Financial Management System ◽  
Financial Administration ◽  
Manual Input ◽  
Financial Software

This study aims to determine the management of the school's financial management system in Madrasah Aliyah Al-mu'awanah and the implementation of Assistant software utilization in the management of the school's financial management system in Al-Mu'awanah Madrasah. This research uses an approach to research and development (R & D) research. Research results show that in practice financial management in Madrasah Aliyah Al-mu'awanah is still based on a manual input data system so that in the process there are obstacles especially in data processing and school financial data recapitulation. Implementation of the use of assistant software in the process of school financial information management provides a positive picture, the statement is reinforced by the presence of a good response from respondents. Based on the distribution of the questionnaire that has been given to the respondents, the percentage of eligibility is 84%. The percentage of feasibility obtained shows that the utilization of computerized software or financial software is feasible to be used as school financial administration software, especially in Madrasah Aliyah Al-Mu'awanah.

scholarly journals Prediction of Prognosis and Survival of Patients with Gastric Cancer by Weighted Improved Random Forest Model

2021 ◽  
Author(s):  
Cheng Xu ◽  
Jing Wang ◽  
TianLong Zheng ◽  
Yue Cao ◽  
Fan Ye
Keyword(s):  
Gastric Cancer ◽  
Random Forest ◽  
Cancer Patient ◽  
Gastric Cancer Patient ◽  
Patient Data ◽  
Random Forest Model ◽  
Average Increase ◽  
Random Forest Algorithm ◽  
Generalization Ability ◽  
Forest Model

IntroductionIt’s very necessary to predict the survival status of patients based on their prognosis. This can assist physicians in evaluating treatment decisions. Random Forest is an excellent machine learning algorithm even without any modification. We propose a new Random Forest weighting method and apply it to the gastric cancer patient data from the Surveillance, Epidemiology, and End Results (SEER) program, and then evaluated the generalization ability of this weighted Random Forest algorithm on 10 public medical datasets. Furthermore, for the same weighting mode, the difference between using out-of-bag (OOB) data and all training sets as the weighting basis is explored.Material and methods110697 cases of gastric cancer patients diagnosed between 1975 and 2016 obtained from the SEER database were contained in the experiment. In addition, 10 public medical datasets are used for the generalization ability evaluation of this weighted Random Forest algorithm.ResultsThrough experimental verification, on the SEER gastric cancer patient data, the weighted Random Forest algorithm improves the accuracy by 0.79% compared with the original Random Forest. In AUC, Macro-averaging increased by 2.32% and Micro-averaging increased by 0.51% on average. Among the 10 public datasets, the Random Forest weighted in accuracy has the best performance on 6 datasets, with an average increase of 1.44% in accuracy and an average increase of 1.2% in AUC.ConclusionsCompared with the original Random Forest, the weighted Random Forest model has a significant improvement in performance, and the effect of using all training data as the weighting basis is better than using OOB data.

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