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Having made friends with a horse, not only was I murdered in a series of murders, I also had a reputation as a beast that was worse than an animal. Retribution comes quickly, I never thought that my fiancée would actually have an affair with my best friend, this is simply preposterous! However, as I continued my search, I realized that this was the truth ...
Anomaly detection is an important topic which has been well‐studied in diverse research areas and application domains. It generally involves detection of abnormal data, unhealthy status, fault diagnosis, and can be helpful to guarantee industrial systems’ stability, security, and economy. As development of intelligent industries and sensor systems grows, large amounts of data become easily available, and challenges arise in industrial systems’ anomaly detection. One typical case is the study within energy‐related systems, like thermal energy, renewable energy study (e.g., wind energy, photovoltaic), electric vehicles, and so on. These systems can involve various data formats and more complex data structures making anomaly data detection a challenge. Currently, under the development of deep learning and big data analytics, many promising results have been achieved in energy systems’ anomaly data detection. However, many challenging problems remain unsolved due to the complex nature of energy industries. New techniques and advanced engineering applications on anomaly detection in energy systems still appeal to a wide range of scholars and industries.
Electric power systems around the world are changing in terms of structure, operation, management and ownership due to technical, financial, and ideological reasons. Power systems keep on expanding in terms of geographical areas, asset additions, and the penetration of new technologies in generation, transmission, and distribution. The conventional methods for solving the power system design, planning, operation, and control problems have been extensively used for different applications, but these methods suffer from several difficulties, thus providing suboptimal solutions. Computationally intelligent methods can offer better solutions for several conditions and are being widely applied in ...
This book is the second volume of proceedings of the 1st Electrical Artificial Intelligence Conference (EAIC 2024). Artificial intelligence and low-carbon economy are two vibrant research fields in the world today. To achieve the goal of carbon neutrality not only signifies a significant transformation in the economic growth mode and a profound adjustment of energy systems but also has equally significant implications for the global economic and social transformation. In the wave of the rapid development of digital economy, artificial intelligence has become an important driving force for promoting high-quality economic and social development. In the path to the “Dual Carbon” goals, whic...
Advances in Energy, Environment and Chemical Engineering collects papers resulting from the conference on Energy, Environment and Chemical Engineering (AEECE 2022), Dali, China, 24-26 June, 2022. The primary goal is to promote research and developmental activities in energy technology, environment engineering and chemical engineering. Moreover, it aims to promote scientific information interchange between scholars from the top universities, business associations, research centers and high-tech enterprises working all around the world. The conference conducts in-depth exchanges and discussions on relevant topics such as energy engineering, environment technology and advanced chemical technolo...
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"A comprehensive quarterly digest and index of all quality Chinese publications in the archeological and art history fields;" includes also translated longer synopses of articles on topics covered, and a report of archeological news.