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Sep 15, 2023Open    Access

Heavy-Head Sampling Strategy of Graph Convolutional Neural Networks for q-Consistent Summary-Explanations with Application to Credit Evaluation Systems

Xinrui Dou
Machine learning systems have found extensive applications as auxiliary tools in domains that necessitate critical decision-making, such as healthcare and criminal justice. The interpretability of these systems’ decisions is of paramount importance to instill trust among users. Recently, there have been developments in globally-consistent rule-based summary-explanation and its max-support (MSGC) problem, enabling the provision of explanations for specific decisions along with pertinent dataset s...
Open Access Library J.   Vol.10, 2023
Doi:10.4236/oalib.1110615


Feb 09, 2023Open    Access

Using Data-Mining to Solve Crimial Cases

Tongxing Li, Yongfeng Zhang, Jiaojiao Zhao, Hui Zhang
Crime is a serious social problem, which affects the improvement of the quality of life and the development of social economy. Under the background of the information age, how to effectively use the collected large amount of crime data to analyze and predict crime is particularly important. Data-mining can extract implicit, unknown and potentially valuable information from a large number of original data. This paper studies how to use data-mining to analyze the intelligence value behind massive ...
Open Access Library J.   Vol.10, 2023
Doi:10.4236/oalib.1109685


Nov 30, 2022Open    Access

Distribution Estimation of Invasive Species Based on Crowdsourcing Reports

Yuxin Shi, Siyuan Liu, Tingzhen Liu
Species invasion will cause certain harm to the local ecosystem. Vespa mandarinia, discovered on Vancouver Island, is harmful to agriculture and predators of European honeybees. The government tried to use a crowdsourcing system to collect information and formulate policies to eliminate Vespa mandarinia. However, the information provided by the local population about Vespa mandarinia is not entirely accurate. For this problem, we build a method to mine trusted informat...
Open Access Library J.   Vol.9, 2022
Doi:10.4236/oalib.1109474


Nov 23, 2021Open    Access

Research on the Application of Big Data Mining in the Construction of Smart Campus

Xianmin Zhang, Jiajia Shen, Peijian Wu, Deliang Sun
With the development of science and technology, the informatization construction of colleges and universities has stepped into the era of big data, and the informatization construction of colleges and universities has changed from digital campus to smart campus. This paper first summarizes the research status from the concept and evolution of the smart campus, the meaning and application of big data and data mining, the characteristics and architecture of the construction of the smart campus, an...
Open Access Library J.   Vol.8, 2021
Doi:10.4236/oalib.1108169


Nov 22, 2021Open    Access

A Taxicab Strong Coverage Station Location Model Based on Big Data of Travel Trajectory

Hui Xiao, Xiaoqian Yu, Yanqiu Cao, Siying Yang, Yu Ge
As traffic congestion has become a common problem plaguing Chinese cities, a strong coverage of taxi stops with reasonable number distribution can not only improve the operating efficiency of taxis, but also make rational use of taxi resources. It can also provide a good waiting experience for passengers, which has important practical significance. Based on the big data of taxi travel trajectory, this paper takes a typical working day in Nanjing as an example, and analyzes the peak travel time b...
Open Access Library J.   Vol.8, 2021
Doi:10.4236/oalib.1108163


Sep 03, 2021Open    Access

The Exploration of the Approach to Data Preparation for Chinese Text Analysis Based on R Language

Jiang Li
This paper explores how to prepare data for analyzing the Chinese texts with R language based on the theory of Welbers, particularly comparing the R package Rwordseg with jiebaR to see the results of Chinese text segmentation at the step of preprocessing.
Open Access Library J.   Vol.8, 2021
Doi:10.4236/oalib.1107821


Apr 15, 2021Open    Access

Web-Based Software for Small Area Estimation under Unit Level Model

James Karangwa, Anshu Bharadwaj
The purpose of this paper is to produce reasonably accurate direct estimators, not only for the characteristics of whole Population but also for a variety of Subpopulations or domains. Many policymakers and researchers also want to obtain statistics for small domains. These small domains are also called small areas, because the sample size in the area or domain from the Survey is small. Due to small sample size, domain-specific direct estimators provide an acceptably large coefficient of variati...
Open Access Library J.   Vol.8, 2021
Doi:10.4236/oalib.1107207


Dec 23, 2020Open    Access

Design of a Quad-Channel Analog Data Acquisition System Based on FPGA

Yongfu Xiao, Hao Zhang, Hao Zou
In order to implement the acquisition and processing of signals from imaging systems, a data acquisition system based on FPGA was designed with the requirements of multi-channel, high-resolution and compactness. The data acquisition (DAQ) system uses a quad-channel 12-bit analog-to-digital converter (ADC) AD9228-65 as the front-end core chip, and a series of signal conditioning circuits to form the front-end system. FPGA is used as the data acquisition, logic control, data readout and processing...
Open Access Library J.   Vol.7, 2020
Doi:10.4236/oalib.1107058


Nov 09, 2020Open    Access

Discussion on the Application of Geographic Information System in Urban Ecological Environment Management under the Background of Big Data

Qinfen Zheng
Urban ecological management in the context of big data space is an objective need for urban development. The ecological environment of a city is a comprehensive group of various ecological factors and ecological relationships that people in urban areas rely on for survival, development, and evolution. Geographic information is performed on the effective management of system technical means. Predictive decision-making and analysis can be made by processing urban spatial data, urban resources, and...
Open Access Library J.   Vol.7, 2020
Doi:10.4236/oalib.1106904


Sep 18, 2020Open    Access

Prediction of Wheat Rust Diseases Using Data Mining Application

Wesenu Bekele Mulatu, Mebratu Fana Bedasa, Gemechu Kena Terefa
Stem rust caused by Puccinia graminis f.sp. tritici and stripe rust caused by Puccinia striiformis are the most destructive wheat rust diseases when environment conditions are favorable in regions where wheat crops are grown. An early prediction mechanism can play a great role in forecasting the occurrence of the rust disease. It assists proactive control and early decision making. However, in the absence of prediction mechanism of wheat rust disease hurried wheat production yield loss more. Hen...
Open Access Library J.   Vol.7, 2020
Doi:10.4236/oalib.1106717


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