Название: Artificial Intelligence and Machine Learning in Smart City PlanningАвтор: Vedik Basetti, Chandan Kumar Shiva
Издательство: Elsevier
Год: 2023
Страниц: 326
Язык: английский
Формат: pdf
Размер: 16.3 MB
Artificial Intelligence and Machine Learning in Smart City Planning shows the reader practical applications of AIML techniques and describes recent advancements in this area in various sectors. Owing to the multidisciplinary nature, this book primarily focuses on the concepts of AIML and its methodologies such as evolutionary techniques, neural networks, machine learning, deep learning, block chain technology, big data analytics, and image processing in the context of smart cities. The text also discusses possible solutions to different challenges posed by smart cities by presenting cutting edge AIML techniques using different methodologies, as well as future directions for those same techniques.
Human beings are the smart and advanced species on this planet because they can think, evaluate, and solve complicated issues. On the other hand, Artificial Intelligence is in the initial stage when compared to human intelligence in many aspects. Then the purpose of Machine Learning is to take decisions based on the data available with efficiency. Research has been going on in technologies like Machine Learning (ML), Artificial Intelligence (AI), and Deep Learning to solve real-world complex issues. The decisions are taken by machines based on the data to automate the process. Some real-world problems use these data-driven decisions, where programing logic cannot be used directly. That is why there is a need for Machine Learning to solve real-world issues with efficacy at a large scale.
Machine Learning is a part of Artificial Intelligence which helps the computer systems to sense the data and take proper decision for forecasting. Machine Learning extracts patterns from raw data by using algorithms. Machine Learning allows computer systems to learn through experience rather than explicitly programmed. Machine learning models consist of learning algorithms which executes some task and enhance their performance over time with experience.
Machine Learning is the fastly expanding technology in the present world. Some researchers named that we are in the golden era of Artificial Intelligence and Machine Learning. Real-world complex problems are solved by the Machine Learning algorithms, which are not resolved with the help of conventional methods in Obulesu et al.. The real-world applications of Machine Learning algorithms are prediction of weather, emotion analysis, detection and prevention of error, sentiment analysis, recognition of object, stock market forecasting, speech synthesis and recognition, customer segmentation, smart city planning, fraud detection and prevention.
Key Features:
- Reviews the smart city concept and teaches how it can contribute to achieving urban development priorities
- Explains soft computing techniques for smart city applications
- Describes how to model problems for effective analysis, intelligent decision making, and optimal operation and control in the smart city paradigm
- Teaches how to carry out independent projects using soft computing techniques in a vast range of areas in diverse fields like engineering, management, and sciences
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