11 research outputs found

    Advances in Optimization and Nonlinear Analysis

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    The present book focuses on that part of calculus of variations, optimization, nonlinear analysis and related applications which combines tools and methods from partial differential equations with geometrical techniques. More precisely, this work is devoted to nonlinear problems coming from different areas, with particular reference to those introducing new techniques capable of solving a wide range of problems. The book is a valuable guide for researchers, engineers and students in the field of mathematics, operations research, optimal control science, artificial intelligence, management science and economics

    Computational Intelligence for Modeling, Control, Optimization, Forecasting and Diagnostics in Photovoltaic Applications

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    This book is a Special Issue Reprint edited by Prof. Massimo Vitelli and Dr. Luigi Costanzo. It contains original research articles covering, but not limited to, the following topics: maximum power point tracking techniques; forecasting techniques; sizing and optimization of PV components and systems; PV modeling; reconfiguration algorithms; fault diagnosis; mismatching detection; decision processes for grid operators

    Pertanika Journal of Science & Technology

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    Pertanika Journal of Science & Technology

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    Heat Exchangers

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    The demand for energy to satisfy the basic needs and services of the population worldwide is increasing as are the economic costs associated with energy production. As such, it is essential to emphasize energy recovery systems to improve heat transfer in thermal processes. Currently, significant research efforts are being conducted to expose criteria and analysis techniques for the design of heat exchange equipment. This book discusses optimization of heat exchangers, heat transfer in novel working fluids, and the experimental and numerical analysis of heat transfer applications

    Applied Metaheuristic Computing

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    For decades, Applied Metaheuristic Computing (AMC) has been a prevailing optimization technique for tackling perplexing engineering and business problems, such as scheduling, routing, ordering, bin packing, assignment, facility layout planning, among others. This is partly because the classic exact methods are constrained with prior assumptions, and partly due to the heuristics being problem-dependent and lacking generalization. AMC, on the contrary, guides the course of low-level heuristics to search beyond the local optimality, which impairs the capability of traditional computation methods. This topic series has collected quality papers proposing cutting-edge methodology and innovative applications which drive the advances of AMC

    Energy Harvesting and Energy Storage Systems

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    This book discuss the recent developments in energy harvesting and energy storage systems. Sustainable development systems are based on three pillars: economic development, environmental stewardship, and social equity. One of the guiding principles for finding the balance between these pillars is to limit the use of non-renewable energy sources

    Applied Methuerstic computing

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    For decades, Applied Metaheuristic Computing (AMC) has been a prevailing optimization technique for tackling perplexing engineering and business problems, such as scheduling, routing, ordering, bin packing, assignment, facility layout planning, among others. This is partly because the classic exact methods are constrained with prior assumptions, and partly due to the heuristics being problem-dependent and lacking generalization. AMC, on the contrary, guides the course of low-level heuristics to search beyond the local optimality, which impairs the capability of traditional computation methods. This topic series has collected quality papers proposing cutting-edge methodology and innovative applications which drive the advances of AMC

    Assessment of Renewable Energy Resources with Remote Sensing

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    The development of renewable energy sources plays a fundamental role in the transition towards a low carbon economy. Considering that renewable energy resources have an intrinsic relationship with meteorological conditions and climate patterns, methodologies based on the remote sensing of the atmosphere are fundamental sources of information to support the energy sector in planning and operation procedures. This Special Issue is intended to provide a highly recognized international forum to present recent advances in remote sensing to data acquisition required by the energy sector. After a review, a total of eleven papers were accepted for publication. The contributions focus on solar, wind, and geothermal energy resource. This editorial presents a brief overview of each contribution.About the Editor .............................................. vii Fernando Ramos Martins Editorial for the Special Issue: Assessment of Renewable Energy Resources with Remote Sensing Reprinted from: Remote Sens. 2020, 12, 3748, doi:10.3390/rs12223748 ................. 1 André R. Gonçalves, Arcilan T. Assireu, Fernando R. Martins, Madeleine S. G. Casagrande, Enrique V. Mattos, Rodrigo S. Costa, Robson B. Passos, Silvia V. Pereira, Marcelo P. Pes, Francisco J. L. Lima and Enio B. Pereira Enhancement of Cloudless Skies Frequency over a Large Tropical Reservoir in Brazil Reprinted from: Remote Sens. 2020, 12, 2793, doi:10.3390/rs12172793 ................. 7 Anders V. Lindfors, Axel Hertsberg, Aku Riihelä, Thomas Carlund, Jörg Trentmann and Richard Müller On the Land-Sea Contrast in the Surface Solar Radiation (SSR) in the Baltic Region Reprinted from: Remote Sens. 2020, 12, 3509, doi:10.3390/rs12213509 ................. 33 Joaquín Alonso-Montesinos Real-Time Automatic Cloud Detection Using a Low-Cost Sky Camera Reprinted from: Remote Sens. 2020, 12, 1382, doi:10.3390/rs12091382 ................. 43 Román Mondragón, Joaquín Alonso-Montesinos, David Riveros-Rosas, Mauro Valdés, Héctor Estévez, Adriana E. González-Cabrera and Wolfgang Stremme Attenuation Factor Estimation of Direct Normal Irradiance Combining Sky Camera Images and Mathematical Models in an Inter-Tropical Area Reprinted from: Remote Sens. 2020, 12, 1212, doi:10.3390/rs12071212 ................. 61 Jinwoong Park, Jihoon Moon, Seungmin Jung and Eenjun Hwang Multistep-Ahead Solar Radiation Forecasting Scheme Based on the Light Gradient Boosting Machine: A Case Study of Jeju Island Reprinted from: Remote Sens. 2020, 12, 2271, doi:10.3390/rs12142271 ................. 79 Guojiang Xiong, Jing Zhang, Dongyuan Shi, Lin Zhu, Xufeng Yuan and Gang Yao Modified Search Strategies Assisted Crossover Whale Optimization Algorithm with Selection Operator for Parameter Extraction of Solar Photovoltaic Models Reprinted from: Remote Sens. 2019, 11, 2795, doi:10.3390/rs11232795 ................. 101 Alexandra I. Khalyasmaa, Stanislav A. Eroshenko, Valeriy A. Tashchilin, Hariprakash Ramachandran, Teja Piepur Chakravarthi and Denis N. Butusov Industry Experience of Developing Day-Ahead Photovoltaic Plant Forecasting System Based on Machine Learning Reprinted from: Remote Sens. 2020, 12, 3420, doi:10.3390/rs12203420 ................. 125 Ian R. Young, Ebru Kirezci and Agustinus Ribal The Global Wind Resource Observed by Scatterometer Reprinted from: Remote Sens. 2020, 12, 2920, doi:10.3390/rs12182920 ................. 147 Susumu Shimada, Jay Prakash Goit, Teruo Ohsawa, Tetsuya Kogaki and Satoshi Nakamura Coastal Wind Measurements Using a Single Scanning LiDAR Reprinted from: Remote Sens. 2020, 12, 1347, doi:10.3390/rs12081347 ................. 165 Cristina Sáez Blázquez, Pedro Carrasco García, Ignacio Martín Nieto, MiguelAngel ´ Maté-González, Arturo Farfán Martín and Diego González-Aguilera Characterizing Geological Heterogeneities for Geothermal Purposes through Combined Geophysical Prospecting Methods Reprinted from: Remote Sens. 2020, 12, 1948, doi:10.3390/rs12121948 ................. 189 Miktha Farid Alkadri, Francesco De Luca, Michela Turrin and Sevil Sariyildiz A Computational Workflow for Generating A Voxel-Based Design Approach Based on Subtractive Shading Envelopes and Attribute Information of Point Cloud Data Reprinted from: Remote Sens. 2020, 12, 2561, doi:10.3390/rs12162561 ................. 207Instituto do Ma
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