scholarly journals Intelligent software system for optimizing adaptive control of investment projecting processes

2020 ◽  
Author(s):  
A. F. Shorikov ◽  
E. V. Butsenko ◽  
V. A. Tyulyukin
2020 ◽  
Vol 15 (89) ◽  
pp. 9-28
Author(s):  
Andrey F. Shorikov ◽  
◽  
Elena V. Butsenko ◽  

The article describes the functionality developed by the authors of an intelligent software system for optimizing adaptive control of business planning processes in the face of uncertainty. The results are based on a new method for optimizing adaptive project management using network economic and mathematical modeling. Based on this method, a methodology has been developed for solving the problem of optimizing adaptive control of business planning processes, which in the proposed intelligent software decision support system uses a block containing an adaptive control optimization model. As the objective function (evaluation functional) in the method used, the value of the length of the time period for the execution of the business plan, which needs to be minimized, is considered. The method used allows you to create a class of acceptable strategies for adaptive control of the implementation process for the business plan in question. Within the framework of this class of strategies, an optimal adaptive control strategy for the implementation of business planning processes is formed, the optimal time for its implementation and the optimal schedule for implementing the business plan as a whole, and the corresponding optimal adaptive control strategies are calculated. Application of the proposed new method in an intelligent software system allows for feedback and optimal time for the implementation of the business project as a whole. The developed intelligent system is designed to automate the modeling of business planning processes and optimize adaptive decision-making control during their implementation on the basis of network economic and mathematical modeling, as well as methods and tools for developing intelligent soft systems. The created system takes into account the existing specific technical and economic conditions and information support. The results obtained in this work can serve as the basis for creating intelligent instrumental systems for supporting managerial decision-making in the implementation of business planning processes in the face of information uncertainty and risks.


2015 ◽  
Vol 5 (5) ◽  
pp. 569-586 ◽  
Author(s):  
Utku Köse ◽  
Aslıhan Tüfekçi

Objective of this work is to introduce an Artificial Intelligence supported educational software system, which has been developed for teaching important subjects of computer programming: algorithm and flowchart concepts, and touch upon the findings, which were obtained for evaluating success of the system. The software system introduced in the work is tightly connected to the rule of teaching essential computer programming concepts, but ensures this task in the context of an Artificial Intelligence supported, intelligent mechanism. In order to have idea about whether the software is an effective teaching tool or not, a general evaluation process has been planned; students subjected to the work have been taken into this process. Findings obtained via evaluation process have shown that the developed software system is successful at effectively teaching the algorithmic thinking logic, which is the essential focus, and algorithm - flowchart concepts. Additionally, it is also possible to express that the software system has improved students' success rates in the courses related to essentials of computer programming and students have found both software and the performed educational processes pretty effective.


2013 ◽  
Vol 380-384 ◽  
pp. 463-466
Author(s):  
Ying Li

A parallel model reference adaptive control system was designed for reaching the optimal control effect and performance in the electrical control system based on the adaptive control theory. The control weighting coefficient was adjusted precisely in real time with the adaptive control theory for the matching and transmission of the self-performance and the out information, and the performance of the control system could reach optimal performance. But on the other hand, the adaptive control theory hadnt is applied in the torpedo control system. An improved electrical control system algorithm was proposed in this system based on the adaptive control theory. The torpedo control system was taken as the example, the parallel model reference adaptive control system was designed. The hardware circuit diagram of the control system was designed. And the control algorithm of the three-channel such as the pitch, yaw and roll of the torpedo control system was designed separately. And the output signal of the system and the software system of the three-channel torpedo control system was simulated. The design result and the simulation result show that the control performance is stable and the software system shows nice performance of human-computer interaction property and good perspective of application performance.


Procedia CIRP ◽  
2019 ◽  
Vol 79 ◽  
pp. 517-522 ◽  
Author(s):  
Nicolas Meier ◽  
Jan Papadoudis ◽  
Anthimos Georgiadis

AI Magazine ◽  
2009 ◽  
Vol 30 (2) ◽  
pp. 17 ◽  
Author(s):  
Chris Urmson ◽  
Chris Baker ◽  
John Dolan ◽  
Paul Rybski ◽  
Bryan Salesky ◽  
...  

The DARPA Urban Challenge was a competition to develop autonomous vehicles capable of safely, reliably and robustly driving in traffic. In this article we introduce Boss, the autonomous vehicle that won the challenge. Boss is complex artificially intelligent software system embodied in a 2007 Chevy Tahoe. To navigate safely, the vehicle builds a model of the world around it in real time. This model is used to generate safe routes and motion plans in both on roads and in unstructured zones. An essential part of Boss’ success stems from its ability to safely handle both abnormal situations and system glitches.


Author(s):  
Gabriela Moise

<p>The computer-assisted learning is a very modern study area, which can be applied to the learning process. The main objective of this paper is to present a software system for online learning based on the intelligent software agents technologies. The main ideas on which this paper is built are: to any person is associated a learning profile (the idea is based on the existence of multiple intelligences, defined by Gardner [3]); the pedagogical resources can be shaped through educational semantic networks or through conceptual maps; a flexible software system in computer assisted learning must be based on the intelligent agents’ technology. The system dedicated to computer-assisted learning must be adapted to the learning profile of each student.<br />The author presents a flexible online teaching software system, which learns to teach according to the learning profile of each student (the author defines this system in the PhD thesis and includes: intelligent agent structures, reward learning algorithms, algorithms to generate plans for an agent).<br />The application includes two agents: the supervising agent and the pedagogical agent, which determines the optimal pedagogical resources for teaching the course. The application has been designed in Microsoft Visual Studio 6.0 and uses Microsoft Agent Technology, which allows vocal recognition. Also, the Protéjé 3.0 software has been used, software that allows building ontology for computer assisted learning. The system has been experimented on the Graph Theory Course, taught at postuniversitary computer science courses, the results proving the necessity of defining a strategy for selecting the pedagogical resources presented to the students according to their learning profile.</p>


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