Alaa Khamis – författare

Each year we witness several paradigm shifts in mobility systems and services, increasingly so as technology progresses. The future of mobility is people-centric, software-defined, connected, and electric. Now more than ever, it is imperative for current and aspiring leaders in the field to understand the foundations of people-centric smart cities with a focus on sustainability.Smart Mobility offers a holistic view of the current and emerging smart mobility systems and explores their foundational technologies, technology enablers, and disruptors. Author Alaa Khamis acknowledges the need for smart mobility arising with growing world urbanization, and the impact of this on public health, congestion, and climate change. Khamis expertly interrogates how a focus on smart mobility can mitigate all of these risks using his triad of complementary factors: technology, governance, and city planning.In this book you’ll study how foundational technologies such as artificial intelligence, blockchain, the Internet of Things, robotics, and many more all work together to allow for smart mobility in our modern era. Khamis additionally covers the topical events of the COVID-19 pandemic and analyzes its impact on consumer behavior and the expected short-term disruptions and longer-term structural changes. The socioeconomic changes in our urban centers are vast, and Smart Mobility breaks down the core concepts with meaningful data and insights.What You Will LearnExplore different mobility modes, including mobility-as-a-service, shared mobility, mobility on demand, the gig economy and the passenger economyCover how the smart mobility triad - technology, governance, and city planning - work together to create a smart and sustainable mobilitySee how the COVID-19 pandemic is impacting consumer behavior and preferences and changing the future of mobilityWho This Book Is ForWorking professionals, students, researchers, technologists, city planners, and the curious layman.

Each year we witness several paradigm shifts in mobility systems and services, increasingly so as technology progresses. The future of mobility is people-centric, software-defined, connected, and electric. Now more than ever, it is imperative for current and aspiring leaders in the field to understand the foundations of people-centric smart cities with a focus on sustainability.

Smart Mobility offers a holistic view of the current and emerging smart mobility systems and explores their foundational technologies, technology enablers, and disruptors. Author Alaa Khamis acknowledges the need for smart mobility arising with growing world urbanization, and the impact of this on public health, congestion, and climate change. Khamis expertly interrogates how a focus on smart mobility can mitigate all of these risks using his triad of complementary factors: technology, governance, and city planning.

In this book you’ll study how foundational technologies such as artificial intelligence, blockchain, the Internet of Things, robotics, and many more all work together to allow for smart mobility in our modern era. Khamis additionally covers the topical events of the COVID-19 pandemic and analyzes its impact on consumer behavior and the expected short-term disruptions and longer-term structural changes. The socioeconomic changes in our urban centers are vast, and Smart Mobility breaks down the core concepts with meaningful data and insights.

What You Will LearnExplore different mobility modes, including mobility-as-a-service, shared mobility, mobility on demand, the gig economy and the passenger economyCover how the smart mobility triad - technology, governance, and city planning - work together to create a smart and sustainable mobilitySee how the COVID-19 pandemic is impacting consumer behavior and preferences and changing the future of mobilityWho This Book Is ForWorking professionals, students, researchers, technologists, city planners, and the curious layman.

Solve design, planning, and control problems using modern machine learning and AI techniques.

In Optimization Algorithms: AI techniques for design, planning, and control problems you will learn:

Machine learning methods for search and optimization problems The core concepts of search and optimization Deterministic and stochastic optimization techniques Graph search algorithms Nature-inspired search and optimization algorithms Efficient trade-offs between search space exploration and exploitation State-of-the-art Python libraries for search and optimization

About the technology:

Search and optimization algorithms are powerful tools that can help practitioners find optimal or near-optimal solutions to a wide range of design, planning and control problems. When you open a route planning app, call for a rideshare, or schedule a hospital appointment, an AI algorithm works behind the scenes to make sure you get an optimized result. This guide reveals the classical and modern algorithms behind these services.

Solve design, planning, and control problems using modern AI techniques.Optimization problems are everywhere in daily life. What’s the fastest route from one place to another? How do you calculate the optimal price for a product? How should you plant crops, allocate resources, and schedule surgeries? Optimization Algorithms introduces the AI algorithms that can solve these complex and poorly-structured problems. In Optimization Algorithms: AI techniques for design, planning, and control problems you will learn: • The core concepts of search and optimization • Deterministic and stochastic optimization techniques • Graph search algorithms • Trajectory-based optimization algorithms • Evolutionary computing algorithms • Swarm intelligence algorithms • Machine learning methods for search and optimization problems • Efficient trade-offs between search space exploration and exploitation • State-of-the-art Python libraries for search and optimization Inside this comprehensive guide, you’ll find a wide range of optimization methods, from deterministic search algorithms to stochastic derivative-free metaheuristic algorithms and machine learning methods. Don’t worry—there’s no complex mathematical notation. You’ll learn through in-depth case studies that cut through academic complexity to demonstrate how each algorithm works in the real world. Plus, get hands-on experience with practical exercises to optimize and scale the performance of each algorithm. About the technology Every time you call for a rideshare, order food delivery, book a flight, or schedule a hospital appointment, an algorithm works behind the scenes to find the optimal result. Blending modern AI methods with classical search and optimization techniques can deliver incredible results, especially for the messy problems you encounter in the real world. This book shows you how. About the book Optimization Algorithms explains in clear language how optimization algorithms work and what you can do with them. This engaging book goes beyond toy examples, presenting detailed scenarios that use actual industry data and cutting-edge AI techniques. You will learn how to apply modern optimization algorithms to real-world problems like pricing products, matching supply with demand, balancing assembly lines, tuning parameters, coordinating mobile networks, and cracking smart mobility challenges. What''s inside • Graph search algorithms • Metaheuristic algorithms • Machine learning methods • State-of-the-art Python libraries for optimization • Efficient trade-offs between search space exploration and exploitation About the reader Requires intermediate Python and machine learning skills. About the author Dr. Alaa Khamis is an AI and smart mobility technical leader at General Motors and a lecturer at the University of Toronto. The technical editor on this book was Frances Buontempo. Table of Contents PART 1 1 Introduction to search and optimization 2 A deeper look at search and optimization 3 Blind search algorithms 4 Informed search algorithms PART 2 5 Simulated annealing 6 Tabu search PART 3 7 Genetic algorithms 8 Genetic algorithm variants PART 4 9 Particle swarm optimization 10 Other swarm intelligence algorithms to explore PART 5 11 Supervised and unsupervised learning 12 Reinforcement learning Appendix A Appendix B Appendix C

This book constitutes the refereed proceedings of the Second International Conference on Autonomous and Intelligent Systems, AIS 2011, held in Burnaby, BC, Canada, in June 2011, colocated with the International Conference on Image Analysis and Recognition, IACIAR 2011. The 40 revised full papers presented were carefully reviewed and selected from 62 submissions. The papers are organized in topical sections on autonomous and intelligent systems, intelligent and advanced control systems, intelligent sensing and data analysis, human-machine interaction, and intelligent circuit analysis and signal processing.