scholarly journals Case Investigation Technology Based on Artificial Intelligence Data Processing

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Jianwei Ding
Keyword(s):  
Artificial Intelligence ◽  
Data Mining ◽  
Decision Making ◽  
Data Processing ◽  
Scientific Basis ◽  
Public Security ◽  
Case Based Reasoning ◽  
Mining Technology ◽  
Case Investigation ◽  
Model Based

Through data mining technology, the hidden information behind a large amount of data is discovered, which can help various management services and provide scientific basis for leadership decision-making. It is an important subject of current police information research. This paper conducts in-depth research on the investigation analysis and decision-making of public security cases and proposes a case-based reasoning model based on two case databases. Moreover, this paper discusses in detail the use of data mining technology to automatically establish a case database, which is a useful exploration and practice for the public security department to establish a new and efficient case investigation auxiliary decision-making system. In addition, this paper studies the method of using data mining technology to assist in the establishment of a case database, analyzes the characteristics of traditional case storage methods, and constructs a case investigation model based on artificial intelligence data processing. The research results show that the model constructed in this paper has certain practical effects.

scholarly journals Analysis of Characteristics of Tennis Singles Matches Based on 5G and Data Mining Technology

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Ming Li ◽  
Qinsheng Li ◽  
Yuening Li ◽  
Yunkun Cui ◽  
Xiufeng Zhao ◽  
...  
Keyword(s):  
Data Mining ◽  
Decision Making ◽  
Statistical Methods ◽  
Analysis Data ◽  
Scientific Basis ◽  
Experimental Simulation ◽  
Mining Technology ◽  
Offensive Tactics ◽  
Analysis System ◽  
Scientific Decision

The level of technical and tactical decision-making in a tennis game has a very important impact on the outcome of the game. How to discover the characteristics and rules of the game from a large amount of technical and tactical data, how to overcome the shortcomings of traditional statistical methods, and how to provide a scientific basis for correct decision-making are a top priority. Based on 5G and association analysis data mining theory, we established a data mining model for tennis technical offensive tactics and association rules and conducted specific case studies. It can calculate the maximization and distribution rate of certain technologies, also distinguish between the athlete’s gain and loss rate and the spatial position on the track, and use artificial statistical methods to cause errors and subjective participation. This solution provides objective and scientific decision support for this problem and is used in the decision-making of the landing point in tennis match technology and tactics. Experimental simulation shows that the data mining technology analysis system used for regional tennis matches is more concise, efficient, and accurate than traditional movie analysis methods.

scholarly journals Ordering Artificial Intelligence Based Recommendations to Tackle the SDGs with a Decision-Making Model Based on Surveys

2021 ◽  
Vol 13 (11) ◽  
pp. 6038
Author(s):  
Sergio Alonso ◽  
Rosana Montes ◽  
Daniel Molina ◽  
Iván Palomares ◽  
Eugenio Martínez-Cámara ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Decision Making ◽  
Sustainable Development Goals ◽  
Modern Society ◽  
Agenda 2030 ◽  
Model Based ◽  
Development Goals ◽  
Sustainability Challenges ◽  
New Research ◽  
Decision Making Model

The United Nations Agenda 2030 established 17 Sustainable Development Goals (SDGs) as a guideline to guarantee a sustainable worldwide development. Recent advances in artificial intelligence and other digital technologies have already changed several areas of modern society, and they could be very useful to reach these sustainable goals. In this paper we propose a novel decision making model based on surveys that ranks recommendations on the use of different artificial intelligence and related technologies to achieve the SDGs. According to the surveys, our decision making method is able to determine which of these technologies are worth investing in to lead new research to successfully tackle with sustainability challenges.

Organizational Data Mining (ODM)

2011 ◽  
pp. 1-8
Author(s):  
Hamid R. Nemati ◽  
Christopher D. Barko
Keyword(s):  
Artificial Intelligence ◽  
Data Mining ◽  
Decision Making ◽  
Information Technology ◽  
Competitive Advantage ◽  
Current Status ◽  
Decision Making Process ◽  
Actionable Knowledge ◽  
The Core ◽  
Mining Tools

An increasing number of organizations are struggling to overcome “information paralysis” — there is so much data available that it is difficult to understand what is and is not relevant. In addition, managerial intuition and instinct are more prevalent than hard facts in driving organizational decisions. Organizational Data Mining (ODM) is defined as leveraging data mining tools and technologies to enhance the decision-making process by transforming data into valuable and actionable knowledge to gain a competitive advantage (Nemati & Barko, 2001). The fundamentals of ODM can be categorized into three fields: Artificial Intelligence (AI), Information Technology (IT), and Organizational Theory (OT), with OT being the core differentiator between ODM and data mining. We take a brief look at the current status of ODM research and how a sample of organizations is benefiting. Next we examine the evolution of ODM and conclude our chapter by contemplating its challenging yet opportunistic future.

Big data based research on the management system framework of ideological and political education in colleges and universities

2020 ◽  
pp. 1-10
Author(s):  
Yuejun Xia
Keyword(s):  
Artificial Intelligence ◽  
Data Mining ◽  
Big Data ◽  
Ideological And Political Education ◽  
Political Education ◽  
Representative Point ◽  
Point Sets ◽  
Mining Technology ◽  
Education Management ◽  
Intelligence System

Artificial intelligence model combined with data mining technology can mine useful data from college ideological and political education management, and conduct process evaluation and teaching management. Therefore, based on the superiority of data mining technology and artificial intelligence system, this paper improves the traditional algorithm and constructs a university ideological and political education management model based on big data artificial intelligence. Moreover, this study uses a local sensitive hash function to generate representative point sets and uses the generated representative point sets for clustering operations. In order to verify the performance of the algorithm model, a control experiment is designed to compare the algorithm of this paper with traditional data mining methods. It can be seen from the research results that the algorithm model constructed in this paper has good performance and can be applied to practice.

scholarly journals Artificial Intelligence-Virtual Trainer: An educative system based on artificial intelligence and designed to produce varied and consistent training lessons

2016 ◽  
Vol 231 (2) ◽  
pp. 110-124 ◽  
Author(s):  
Julien Henriet
Keyword(s):  
Artificial Intelligence ◽  
Decision Making ◽  
Ordered Set ◽  
Case Based Reasoning ◽  
Adaptation Process ◽  
Multi Agent System ◽  
Multi Agent ◽  
Different Parts ◽  
Case Based ◽  
Underlying Theme

AI-Virtual Trainer is an educative system using Artificial Intelligence to propose varied lessons to trainers. The agents of this multi-agent system apply case-based reasoning to build solutions by analogy. However, as required by the field, Artificial Intelligence-Virtual Trainer never proposes the same lesson twice, whereas the same objective may be set many times consecutively. The adaptation process of Artificial Intelligence-Virtual Trainer delivers an ordered set of exercises adapted to the objectives and sub-objectives chosen by trainers. This process has been enriched by including the notion of distance between exercises: the proposed tasks are not only appropriate but are hierarchically ordered. With this new version of the system, students are guided towards their objectives via an underlying theme. Finally, the agents responsible for the different parts of lessons collaborate with each other according to a dedicated protocol and decision-making policy since no exercise must appear more than once in the same lesson. The results prove that Artificial Intelligence-Virtual Trainer, however perfectible, meets the requirements of this field.

Application of Dynamic Data Mining and Case-Based Reasoning in the Drilling Fault Diagnosis

2012 ◽  
Vol 524-527 ◽  
pp. 1350-1354
Author(s):  
Qi Li ◽  
Peng Zhai ◽  
Yun Li Zhao
Keyword(s):  
Data Mining ◽  
Fault Diagnosis ◽  
Knowledge Base ◽  
Case Based Reasoning ◽  
Dynamic Data ◽  
Mining Technology ◽  
Decision Systems ◽  
Static Data ◽  
Fault Diagnosis System ◽  
Case Based

Most of the traditional drilling fault diagnosis & decision systems use static data mining technology, so the update of knowledge base becomes its bottlenecks in its development. In order to meet the actual needs, this paper puts forward the method, which combines dynamic data mining technology with case-based reasoning technology, to design drilling fault diagnosis & decision systems. First, design drilling fault diagnosis system overall, then describe the realization of how to realize dynamic data mining and case-based reasoning in detail, finally, introduce some question about the update of knowledge base.

Data Mining Technology Applications in Tobacco Commercial Enterprise

2012 ◽  
Vol 461 ◽  
pp. 418-420
Author(s):  
Yi Min Mo ◽  
Xin Shun Tong ◽  
Li Hua Yang
Keyword(s):  
Data Mining ◽  
Data Processing ◽  
Demand Forecasting ◽  
Customer Relationship ◽  
Complex Data ◽  
Market Demand ◽  
Mining Technology ◽  
Technology Applications ◽  
Commercial Enterprise ◽  
Key Issues

The wide application of information technology has greatly improve the work efficiency but also caused a large and complex data accumulation. How to get the valuable information from vast amounts of data are the key issues in data processing. This paper studied the application of data mining technology in tobacco commercial enterprise from three aspects: market demand forecasting, customer relationship management and historical data processing. Analysis of how to use data mining technology to make full use of large amounts of data to provide a basis for tobacco commercial enterprise’s decision-making.

The Safety Monitoring of Colliery Equipments Based on Data Mining Technology

2011 ◽  
Vol 128-129 ◽  
pp. 731-734
Author(s):  
Shu Fang Zhao ◽  
Li Chao Chen
Keyword(s):  
Data Mining ◽  
Decision Making ◽  
Essential Role ◽  
Scientific Information ◽  
Safety Monitoring ◽  
Monitoring Data ◽  
Mining Technology ◽  
Use Of Data ◽  
Stochastic Data

Data mining is the process of abstracting unaware, potential and useful information and knowledge from plentiful, incomplete, noisy, fuzzy and stochastic data. The reliability of colliery equipments takes an essential role in the safety of production. Not only since their continuance of operation, had the accumulation of historical error data of colliery equipments resulted in a mass of surplus data, but also because their lacks of helpful information, which as a result makes colliery managers as well as equipment operators hard to make decisions. Seeing that, we introduced ways here that makes use of data mining technology by processing and analyzing historical monitoring data, recognizing and extracting meaningful patterns so as to provide scientific information for decision-making on the safety of colliery operations, which would help for the forecasting of potential threatens of colliery equipments’ operation, thus, make great contributions to prevent disasters from happening.

scholarly journals Sistem Cerdas Permainan Papan The Battle Of Honor dengan Decision Making dan Machine Learning

2021 ◽  
Vol 12 (2) ◽  
pp. 136
Author(s):  
Arnan Dwika Diasmara ◽  
Aditya Wikan Mahastama ◽  
Antonius Rachmat Chrismanto
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Decision Making ◽  
Intelligent System ◽  
Third Party ◽  
Case Based Reasoning ◽  
Board Game ◽  
Rule Based ◽  
Case Based ◽  
Rule Based Systems

Abstract. Intelligent System of the Battle of Honor Board Game with Decision Making and Machine Learning. The Battle of Honor is a board game where 2 players face each other to bring down their opponent's flag. This game requires a third party to act as the referee because the players cannot see each other's pawns during the game. The solution to this is to implement Rule-Based Systems (RBS) on a system developed with Unity to support the referee's role in making decisions based on the rules of the game. Researchers also develop Artificial Intelligence (AI) as opposed to applying Case-Based reasoning (CBR). The application of CBR is supported by the nearest neighbor algorithm to find cases that have a high degree of similarity. In the basic test, the results of the CBR test were obtained with the highest formulated accuracy of the 3 examiners, namely 97.101%. In testing the AI scenario as a referee, it is analyzed through colliding pieces and gives the right decision in determining victoryKeywords: The Battle of Honor, CBR, RBS, unity, AIAbstrak. The Battle of Honor merupakan permainan papan dimana 2 pemain saling berhadapan untuk menjatuhkan bendera lawannya. Permainan ini membutuhkan pihak ketiga yang berperan sebagai wasit karena pemain yang saling berhadapan tidak dapat saling melihat bidak lawannya. Solusi dari hal tersebut yaitu mengimplementasikan Rule-Based Systems (RBS) pada sistem yang dikembangkan dengan Unity untuk mendukung peran wasit dalam memberikan keputusan berdasarkan aturan permainan. Peneliti juga mengembangkan Artificial Intelligence (AI) sebagai lawan dengan menerapkan Case-Based reasoning (CBR). Penerapan CBR didukung dengan algoritma nearest neighbour untuk mencari kasus yang memiliki tingkat kemiripan yang tinggi. Pada pengujian dasar didapatkan hasil uji CBR dengan accuracy yang dirumuskan tertinggi dari 3 penguji yaitu 97,101%. Pada pengujian skenario AI sebagai wasit dianalisis lewat bidak yang bertabrakan dan memberikan keputusan yang tepat dalam menentukan kemenangan.Kata Kunci: The Battle of Honor, CBR, RBS, unity, AI

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