中世纪军事行动中用于计算战斗和非战斗损失的基于网络的决策支持系统

O. Melnykov, Andrei Kapeleshchuk
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摘要

该项目致力于使用人工智能方法计算中世纪军队的损失数量。本文考虑了几种可能的计算方法,并分析了历史资料。对影响战斗和非战斗损失的因素进行了分析,对科学和科普文献进行了分析,并将专家提出的方法翻译成公式语言。考虑了神经网络的构建、结构的选择、训练样本数据的搜索和合成过程,以及对得到的数据进行训练和验证的过程。开发了未来web应用的两个神经网络模型和一个UML图形式的信息模型。描述了web系统的每个元素的用例图、类图和组件图。这些模型是使用现代Django框架实现的。已经开发并测试了一个具有微博客功能的成熟web应用程序。对所开发的系统的效率和可扩展性进行了总结,并通过一个真实的历史实例对系统的功能进行了验证。该项目开发了一个信息系统模型,用于分析部队数量和计算遥远过去的军事损失。已经描述了数学模型,分析了历史来源,并使用UML建模语言创建了应用程序的详细模型,这允许您在建模阶段详细地理解其接口。基于在历史文献分析中获得的数据,已经开发出神经网络架构来确定中世纪军队的非战斗损失,并根据参与战斗的武装部队每个分支的士兵数量的数据确定战斗损失。开发了用于计算战斗和非战斗损失的Web应用程序,开发了用于发布系统新闻的界面设计和小块。蒙古军队在西征的第一个月(1236年)所遭受的非战斗损失被计算为例子。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
WEB-BASED SYSTEM of DECISION SUPPORT FOR CALCULATING COMBAT AND NON-COMBAT LOSSES DURING MILITARY CAMPAIGNS IN THE MIDDLE AGES
The project is devoted to calculating the number of losses of medieval armies using artificial intelligence methods. Several possible calculation methods have been considered, and historical sources have been analyzed. The analysis of factors that affected combat and non-combat losses and the analysis of scientific and popular science literature have been carried out, and the methods proposed by specialists have been translated into the language of formulas. The process of building neural networks, selecting their architecture, searching and synthesizing data for training samples have been considered, and the process of training and verifying the obtained data have been considered. Two models of neural networks and an information model in the form of UML diagrams of the future web application have been developed. Diagrams of use cases, classes, and components for each element of the web system have been described. The models have been implemented using the modern Django framework. A full-fledged web application with microblogging has been developed and tested. The conclusions have been drawn about the efficiency and scalability of the developed system, and the functionality of the system has been demonstrated using a real historical example. The project has developed the models of an information system for analyzing the number of troops and calculating military losses of the remote past. Mathematical models have been described, historical sources have been analyzed, and detailed models of the application have been created using the UML modeling language, which allows you to understand its interface in detail at the modeling stage. Based on the data obtained in the analysis of historical literature, the neural network architectures have been developed to determine non-combat losses in the medieval army and determine combat losses based on the data on the number of each branch’s soldiers of the armed forces who were involved during the battle. Web applications for calculating combat and non-combat losses have been developed, interface design and mini-block for publishing system News have been developed either. The non-combat losses suffered by the Mongol army in the first month of the Western campaign (1236) have been calculated as the example.
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