roy arup (8 Ergebnisse)

Zustand: New. This is a Brand-new US Edition. This Item may be shipped from US or any other country as we have multiple locations worldwide.

Paperback. Zustand: Brand New. 164 pages. 8.66x5.91x0.37 inches. In Stock.

Taschenbuch. Zustand: Neu. Developing Hybrid Intelligence Based Recommender System: | A Search Towards Machine Learning Components | Arup Roy (u. a.) | Taschenbuch | Englisch | 2023 | LAP LAMBERT Academic Publishing | EAN 9786206155256 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.

Buch. Zustand: Neu. Neuware - This book is an effort made to consolidate his learning from life through simple real life stories and bring out management lesson learning from each stage of his life so that the future generation which is aspiring to climb the new height in today's Corporate World both as entrepreneur and Employee may noy having to 'Reinvent the Wheel'.

Zustand: new.

Paperback. Zustand: Brand New. 157 pages. 9.75x7.50x0.50 inches. In Stock.

Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book discusses machine learning and AI in real-time image processing for road transportation and traffic management. There is a growing need for affordable solutions that make use of cutting-edge technology like artificial intelligence (AI), machine learning (ML), and the Internet of Things (IoT). The efficiency, sustainability, and safety of transport networks can be greatly increased by implementing an Internet of Things (IoT) and machine learning (ML)-based smart road transport system. Install sensors on roadways and intersections to gather data on traffic conditions in real time, such as vehicle density, speed, and flow. Predicting traffic patterns is done by analyzing the gathered data using machine learning algorithms. This can lessen traffic, enhance overall traffic management, and optimize traffic signal timings. Vehicles equipped with Internet of Things devices can have their health monitored in real time. Parameters including lane changes, brake condition, tire pressure, and engine performance can all be monitored by sensors. Based on the gathered data, ML models are used to forecast probable maintenance problems. By scheduling preventive maintenance, failures can be avoided and overall road safety can be increased. Create a smartphone app that would enable drivers to locate parking spots in their area. To forecast parking availability based on past data, the time of day, and special events, apply machine learning algorithms. Integrate Internet of Things (IoT) sensors into fleet vehicles to monitor their performance, location, and fuel consumption. To maximize fleet efficiency, reduce fuel consumption, and plan routes more effectively, apply machine learning algorithms. Train ML models to forecast the quickest and most efficient routes with the help of historical data analysis. Route recommendations for drivers or fleet management systems can be constantly adjusted with real-time updates, which contain real-time data on road conditions, accidents, and construction. To guarantee smooth integration and efficient implementation, government organizations, transportation providers, and technology firms must work together.

Hardcover. Zustand: Brand New. 244 pages. 9.25x6.10x9.21 inches. In Stock.