Artificial intelligence in a value based management system

1988 ◽  
Vol 1 (1) ◽  
pp. 27-33
Author(s):  
S. A. Sora
Keyword(s):  
Artificial Intelligence ◽  
Management System ◽  
Value Based Management ◽  
A Value

A value-based management system

1996 ◽  
Vol 39 (5) ◽  
pp. 48-52 ◽  
Author(s):  
Stanley F. Slater ◽  
Eric M. Olson
Keyword(s):  
Management System ◽  
Value Based Management ◽  
A Value

scholarly journals Building a value-based human resource management system

2021 ◽  
Vol 273 ◽  
pp. 08010
Author(s):  
Tatiana Gaponenko ◽  
Viktoriya Dovbysh ◽  
Nikolay Filin ◽  
Raykhana Bulatova
Keyword(s):  
Personnel Management ◽  
Management System ◽  
Direct Method ◽  
Investment Project ◽  
Expert Assessment ◽  
Individual Values ◽  
Corporate Values ◽  
Value Based Management ◽  
A Value ◽  
The Impact

The aim of the study is to develop a value-based approach to the management of organizational staff, which involves the management of employee behaviour through the development of a commitment to corporate values, which will improve the quality and efficiency of the management. The methods of analogy, expert assessment, estimating the efficiency of the investment project, the coefficient method, the direct method of estimating the value of human capital by the cost approach are used. The result of the study is a methodology for studying corporate and personal values, as well as a system of indicators to measure the effectiveness of decisions taken in the area of value-based personnel management. It is proposed to measure the impact of value-based staff management in three ways: by the results achieved through the commitment to individual values; as a degree of achievement of management objectives; as the efficiency of investment in personnel. The system of value-based personnel management presented was tested in the context of an agricultural organization, for which it was proposed that the personnel management system be reoriented from goal-based management to value-based management. The effectiveness of the proposed solutions has been assessed through the developed system of indicators.

Implementasi Algoritma Dijkstra Pada Game Pacman

CCIT Journal ◽  
2019 ◽  
Vol 12 (2) ◽  
pp. 170-176
Author(s):  
Anggit Dwi Hartanto ◽  
Aji Surya Mandala ◽  
Dimas Rio P.L. ◽  
Sidiq Aminudin ◽  
Andika Yudirianto
Keyword(s):  
Artificial Intelligence ◽  
Greedy Algorithm ◽  
Dijkstra Algorithm ◽  
Testing Phase ◽  
A Value ◽  
Route Problem ◽  
Starting Point ◽  
The Greedy Algorithm

Pacman is one of the labyrinth-shaped games where this game has used artificial intelligence, artificial intelligence is composed of several algorithms that are inserted in the program and Implementation of the dijkstra algorithm as a method of solving problems that is a minimum route problem on ghost pacman, where ghost plays a role chase player. The dijkstra algorithm uses a principle similar to the greedy algorithm where it starts from the first point and the next point is connected to get to the destination, how to compare numbers starting from the starting point and then see the next node if connected then matches one path with the path). From the results of the testing phase, it was found that the dijkstra algorithm is quite good at solving the minimum route solution to pursue the player, namely by getting a value of 13 according to manual calculations

Research on the framework of university ideological and political education management system based on artificial intelligence

2021 ◽  
pp. 1-10
Author(s):  
Xuying Sun ◽  
Yu Zhang
Keyword(s):  
Artificial Intelligence ◽  
Political Theory ◽  
Outlier Detection ◽  
Management System ◽  
Detection Algorithm ◽  
Colleges And Universities ◽  
Ideological And Political Education ◽  
Political Education ◽  
Data Simulation ◽  
Artificial Intelligence Technology

The importance of the management of ideological and political theory courses in colleges and universities is objective to the importance of ideological and political theory courses. At present, the management of ideological and political theory courses in colleges and universities has big problems in both macro and micro aspects. This paper combines artificial intelligence technology to build an intelligent management system for ideological and political education in colleges and universities based on artificial intelligence, and conducts classroom supervision through intelligent recognition of student status. The KNN outlier detection algorithm based on KD-Tree is proposed to extract the state information of class students. Through data simulation, it can be known that the KD-KNN outlier detection algorithm proposed in this paper significantly improves the efficiency of the algorithm while ensuring the accuracy of the KNN algorithm classification. Through experimental research, it can be seen that the construction of this system not only clarifies the direction of management from a macro perspective, but also reveals specific methods of management from a micro perspective, and to a certain extent effectively solves the problems in the management of ideological and political theory courses in colleges and universities.

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