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The Global ETD Search service is a free service for researchers
to find electronic theses and dissertations. This service is
provided by the
Networked Digital Library of Theses and Dissertations.
Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
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Showing 41 to 42 of 42 (0.01 seconds)Spelling suggestions: "subject:"интеллект"" "subject:"интеллекта""
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Разработка инвестиционного проекта по автоматизации бизнес-процессов на предприятии ресторанного бизнеса : магистерская диссертация / Development of an investment project for the automation of business processes at a restaurant business enterpriseБахшиев, Ф. Р., Bakhshiev, F. R. January 2021 (has links)
Магистерская диссертация посвящена разработке инвестиционного проекта по автоматизации проблемных бизнес-процессов на предприятии ресторанного бизнеса. Большое внимание в диссертации уделено установлению и обоснованию перечня требований для выбора системы автоматизации предприятия ресторанного бизнеса, определению этапов схемы автоматизации бизнес-процессов предприятия при его присоединении к экосистеме. В результате исследования разработана методология автоматизации внешних бизнес-процессов предприятия при его присоединении к экосистеме, определен состав разделов бизнес-плана инвестиционного проекта, в наилучшей степени отвечающего проектам автоматизации бизнес-процессов предприятия. / The master's thesis is devoted to the development of an investment project for the automation of problematic business processes in the restaurant business enterprise. The dissertation focuses on the establishment and justification of the list of requirements for choosing the automation system of the restaurant business enterprise, determining the stages of the automation scheme of business processes of the enterprise when it joins the ecosystem. As a result of the study, a methodology for automating external business processes of an enterprise when it joins the ecosystem was developed, and the composition of the sections of the business plan of an investment project that best meets the projects of automating business processes of an enterprise was determined.
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Dynamic Speed Adaptation for Curves using Machine Learning / Dynamisk hastighetsanpassning för kurvor med maskininlärningNarmack, Kirilll January 2018 (has links)
The vehicles of tomorrow will be more sophisticated, intelligent and safe than the vehicles of today. The future is leaning towards fully autonomous vehicles. This degree project provides a data driven solution for a speed adaptation system that can be used to compute a vehicle speed for curves, suitable for the underlying driving style of the driver, road properties and weather conditions. A speed adaptation system for curves aims to compute a vehicle speed suitable for curves that can be used in Advanced Driver Assistance Systems (ADAS) or in Autonomous Driving (AD) applications. This degree project was carried out at Volvo Car Corporation. Literature in the field of speed adaptation systems and factors affecting the vehicle speed in curves was reviewed. Naturalistic driving data was both collected by driving and extracted from Volvo's data base and further processed. A novel speed adaptation system for curves was invented, implemented and evaluated. This speed adaptation system is able to compute a vehicle speed suitable for the underlying driving style of the driver, road properties and weather conditions. Two different artificial neural networks and two mathematical models were used to compute the desired vehicle speed in curves. These methods were compared and evaluated. / Morgondagens fordon kommer att vara mer sofistikerade, intelligenta och säkra än dagens fordon. Framtiden lutar mot fullständigt autonoma fordon. Detta examensarbete tillhandahåller en datadriven lösning för ett hastighetsanpassningssystem som kan beräkna ett fordons hastighet i kurvor som är lämpligt för förarens körstil, vägens egenskaper och rådande väder. Ett hastighetsanpassningssystem för kurvor har som mål att beräkna en fordonshastighet för kurvor som kan användas i Advanced Driver Assistance Systems (ADAS) eller Autonomous Driving (AD) applikationer. Detta examensarbete utfördes på Volvo Car Corporation. Litteratur kring hastighetsanpassningssystem samt faktorer som påverkar ett fordons hastighet i kurvor studerades. Naturalistisk bilkörningsdata samlades genom att köra bil samt extraherades från Volvos databas och bearbetades. Ett nytt hastighetsanpassningssystem uppfanns, implementerades samt utvärderades. Hastighetsanpassningssystemet visade sig vara kapabelt till att beräkna en lämplig fordonshastighet för förarens körstil under rådande väderförhållanden och vägens egenskaper. Två olika artificiella neuronnätverk samt två matematiska modeller användes för att beräkna fordonets hastighet. Dessa metoder jämfördes och utvärderades.
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