This book is the result of works dedicated to specific applications of metaheuristics in smart electrical grids. From electric transmission, distribution networks to electric microgrids, the notion of intelligence refers to the ability to propose acceptable solutions in an increasingly more restrictive environment. Most often, it refers to decision-making assisting tools designed to support all human action.
标签： Metaheuristics Intelligent Electrical Networks for
上传时间： 2020-06-07
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n present power system, the engineers face variety of challenges in planning, construction and operation. In some of the problems, the engineers need to use managerial talents. In system design or upgrading the entire system into automatic control instead of slow response of human operator, the engineers need to exercise more technical knowledge and experience. It is principally the engi- neer’s ability to achieve the success in all respect and provide the reliable and uninterrupted service to the customers. This chapter covers some important areas of the traditional power system that helps engineers to overcome the challenges. It emphasizes the characteristics of the various components of a power system such as generation, transmission, distribution, protection and SCADA system. During normal operating conditions and disturbances, the acquired knowledge will pro- vide the engineers the ability to analyse the performance of the complex system and execute future improvement
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Radio frequency identification (RFID) is a type of automatic identification systems which has gained popularity in recent years for being fast and reliable in keeping track of the individual objects. In RFID systems, contactless object identification is achieved using radio signals without the need for physical contact as the case with other existing identification technologies such as barcodes. Therefore, a huge number of items can be identified in a short amount of time with high reliability and low cost which makes the RFID technology very attractive for a wide range of applications such as supply chain management, e-health, monitoring humans, pets, animals, and many other objects, toll control, and electrical tagging. Furthermore, RFID technology eliminates the human error and reduces the total cost of the products.
上传时间： 2020-06-08
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To a quantum mechanic the whole universe is one godawful big interacting wavefunction ? but to the rest of us, it’s a world full of separate and distinguishable objects that hurt us when we kick them. At a few months of age, human children recognize objects, expect them to be permanent and move continuously, and display surprise when they aren’t or don’t. We associate visual, tactile, and in some cases audible and olfactory sensations with identifiable physical things. We’re hardwired to understand our environment as being composed of separable things with specific properties and locations. We understand the world in terms of what was where when.
上传时间： 2020-06-08
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Control systems are becoming more important every day. At the beginning, the in- dustry used sequential controls for solving a lot of industrial applications in control systems, and then the linear systems gave us a huge increase in applying automatic linear control on industrial application. One of the most recent methods for control- ling industrial applications is intelligent control, which is based on human behavior or concerning natural process.
标签： Intelligent Control Systems LabVIEW with
上传时间： 2020-06-10
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If you are acquainted with neural networks, automatic control problems are good industrial applications and have a dynamic or evolutionary nature lacking in static pattern-recognition; control ideas are also prevalent in the study of the natural neural networks found in animals and human beings. If you are interested in the practice and theory of control, artificial neu- ral networks offer a way to synthesize nonlinear controllers, filters, state observers and system identifiers using a parallel method of computation.
标签： Control Systems Neural For
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Signals convey information. Systems transform signals. This book introduces the mathe- matical models used to design and understand both. It is intended for students interested in developing a deep understanding of how to digitally create and manipulate signals to measure and control the physical world and to enhance human experience and communi- cation.
标签： Interpretation Structure and Signals Systems of
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Modern information technologies and the advent of machines powered by artificial intelligence (AI) have already strongly influenced the world of work in the 21st century. Computers, algorithms and software simplify everyday tasks, and it is impossible to imagine how most of our life could be managed without them. However, is it also impossible to imagine how most process steps could be managed without human force? The information economy characterised by exponential growth replaces the mass production industry based on economy of scales
标签： AI-and-Robotics-IBA-GEI-April 2017
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The past decade has seen an explosion of machine learning research and appli- cations; especially, deep learning methods have enabled key advances in many applicationdomains,suchas computervision,speechprocessing,andgameplaying. However, the performance of many machine learning methods is very sensitive to a plethora of design decisions, which constitutes a considerable barrier for new users. This is particularly true in the booming field of deep learning, where human engineers need to select the right neural architectures, training procedures, regularization methods, and hyperparameters of all of these components in order to make their networks do what they are supposed to do with sufficient performance. This process has to be repeated for every application. Even experts are often left with tedious episodes of trial and error until they identify a good set of choices for a particular dataset.
标签： Auto-Machine-Learning-Methods-Sys tems-Challenges
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We’re living through exciting times. The landscape of what computers can do is changing by the week. Tasks that only a few years ago were thought to require higher cognition are getting solved by machines at near-superhuman levels of per- formance. Tasks such as describing a photographic image with a sentence in idiom- atic English, playing complex strategy game, and diagnosing a tumor from a radiological scan are all approachable now by a computer. Even more impressively, computers acquire the ability to solve such tasks through examples, rather than human-encoded of handcrafted rules.
标签： Deep-Learning-with-PyTorch
上传时间： 2020-06-10
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