genetic algorithm

According to the architecture document of intelligentization of armed forces intelligence, reducing the physical presence of operational forces by using new technologies and digital empowerment in operational actions such as: pursuit and surveillance, is one of the goals of counter-intelligence organizations. One of the smart tools to realize this is the design and implementation of facial recognition systems, which have faced many complications due to the use of different image processing techniques simultaneously and the high similarity of human face images in massive databases. In order to overcome these problems and make it possible to recognize faces in massive databases of over 500,000 images, while explaining the Big-GAK algorithm, we will provide an intelligent mechanism including the following steps: 1. Feature extraction in interaction with pre-processing and quality control cognitive units.  2. Classification using cognitive algorithms and genetic algorithms.  3. Applying local LBP algorithm and K-Points algorithm to reduce the range of images and then accurate diagnosis.  4. Verification by an observer and referral to the second stage of the genetic algorithm in case of failure.

The allocation of limited resources in the military field is an important challenge that seeks to maximize or minimize. Game theory is used to define resources in terms of conflict and definitions. One of the game theory research issues is Blato's Syringe game, which aims to allocate strategic resources.
In this game, two players are given limited resources on a fixed number of battlefields, without knowledge of the opponent's decisions. In this article, this issue is solved by examining the genetic algorithm, which is a meta-heuristic algorithm.
On the other hand, by introducing the brute-force algorithm and solving all situations, a comparison has been made with the genetic algorithm in terms of execution time and optimality of resource allocation. According to the concluded data, the genetic algorithm works in this problem in 47% of the time similar to the brute-force algorithm and in 42% of the time it works better.
Using the Python programming language and the Django software framework, the Colonel Blato game simulator has been designed and implemented on the web platform, which includes user management pages, game creation, game list and game guide. This simulator has the ability to create problems and choose an opponent as another user, random allocation and genetic algorithm.

The price movement strategy is more about finding return levels and ranges. These ranges can be the return of trend correction or market return due to the end of the trend or the return of the market from the floor or ceiling of the oscillation range. , is. In terms of its objectives, the present study is an applied research, which means that it seeks to gain the necessary knowledge to determine the means by which stakeholders need to consider very important points, including identifying turning points in purchasing decisions and Sales are crucial, get rid of them. Also, since we seek to find relationships between variables in order to identify return points and evaluate the impact of their changes on the overall result, this study in terms of how to do it; It will be a causal or experimental research. Also in terms of data type, it will be a research with little data. Also, from the point of view of implementation time, it is a cross-sectional research followed by futurism. In this research, fuzzy logic and genetic algorithm were used to provide a method for identifying return points in financial markets. For this purpose, a mamdani fuzzy system has been used. . After implementing the proposed structure, the evaluation of the optimized membership functions was performed in order to ensure that these functions are in line with the desired research (determination of return points).

The present paper is conducted with the aim of identifying and prioritizing the challenges confronting strategic management in a defense industry and has used content analysis and interviewing tool to identify the challenges facing the strategic management of that defense industry and has also used the questionnaire instrument to confirm the main challenges and its reliability was estimated to be 0.92. For sampling interview, the method of theoretical adequacy of the data was used. The results of the research showed that existence of a kind of divergent thinking in collecting data, lack of specification about the responsibility of individuals in implementing changes in the organization, lack of employee alignment, lack of proper allocation of resources, failure to identify the obstacles ahead in implementing the strategy, lack of commitment to management, failure to transfer the strategy, manager's attention to maintaining the status quo in the organization, the misconception of some managers about the situation are among the challenges in the strategic management of the defense industry. Then, these challenges are ranked by permutation and genetic algorithm and the most important factor is the existence of a divergent thinking in data collection and the least important factor is the lack of management commitment.