Advances on computational intelligence in energy : the applications of nature-inspired metaheuristic algorithms in energy

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Titel
Advances on computational intelligence in energy the applications of nature-inspired metaheuristic algorithms in energy
verantwortlich
Herawan, Tutut (VerfasserIn); Chiroma, Haruna (VerfasserIn); Abawajy, Jemal H. (VerfasserIn)
veröffentlicht
Cham, Switzerland: Springer Nature, [2019]
©2019
Erscheinungsjahr
2019
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Green energy and technology.
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British Library Catalogue
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245 1 0 |a Advances on computational intelligence in energy  |b the applications of nature-inspired metaheuristic algorithms in energy  |c Tutut Herawan, Haruna Chiroma and Jemal H. Abawajy 
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505 0 |a Intro; Preface; Reviewers; GET Authors; Contents; A Theoretical Framework for Big Data Analytics Based on Computational Intelligent Algorithms with the Potential to Reduce Energy Consumption; 1 Introduction; 2 Computational Intelligent Algorithms; 2.1 Characteristics of Computational Intelligent Algorithms; 3 Big Data Analytics and Energy Consumption by Cluster Computing Systems; 3.1 Big Data Analytics Platforms; 3.2 Energy Consumption Over Big Data Platforms; 3.3 Metrics Used for Measuring Power in Big Data Platforms; 4 Computational Intelligent Algorithms and Big Data Analytics 
505 8 |a 5 Energy Consumption in the Application of Computational Intelligent Algorithms in Big Data Analytics6 A Proposed Framework for Big Data Analytics Using Computational Intelligent Algorithms; 7 Conclusions; References; Artificial Bee Colony for Minimizing the Energy Consumption in Mobile Ad Hoc Network; 1 Introduction; 2 Energy-Aware Routing Protocol; 3 Routing Protocols in MANET; 3.1 Destination-Sequenced Distance-Vector Routing; 3.2 Ad Hoc On-Demand Distance-Vector Routing Protocol; 4 Artificial Bee Colony for AODV and DSDV; 5 Experimental Results; 5.1 Simulation Settings 
505 8 |a 5.2 Performance Metrics5.3 Simulation Results and Performance Comparison; 6 Conclusion; References; A Novel Chicken Swarm Neural Network Model for Crude Oil Price Prediction; 1 Introduction; 2 Artificial Neural Network; 3 Chicken Swarm Optimization; 4 The Proposed Chicken S-NN Algorithm; 5 Results & Discussion; 5.1 Preliminaries; 5.2 Data; 5.3 Discussion; 6 Conclusion; References; Forecasting OPEC Electricity Generation Based on Elman Network Trained by Cuckoo Search Algorithm; 1 Introduction; 2 Elman Network; 3 Cuckoo Search; 4 The Proposed CS Elman Algorithm; 5 Results and Discussion 
505 8 |a 5.1 Discussion6 Conclusions; References; Variable Neighborhood Search-Based Symbiotic Organisms Search Algorithm for Energy-Efficient Scheduling of Virtual Machine in Cloud Data Center; 1 Introduction; 2 Related Works; 3 Energy-Efficient Virtual Machine Scheduling Optimization; 3.1 Problem Definition; 3.2 Basic Concepts of Symbiotic Organisms Search; 4 Performance Evaluation; 4.1 Experimental Setup; 4.2 Results and Discussion; 5 Conclusion and Future Work; References; Energy Savings in Heterogeneous Networks with Self-Organizing Backhauling; 1 Introduction 
505 8 |a 2 Base Station Types in HETNET and Power System Consideration2.1 Base Station Types in HetNet; 2.2 Power System Consideration of BS Sites; 3 Small Cells Deployment and Backhauling Options; 3.1 Wired Backhaul Options for Small Cells; 3.2 Wireless Backhaul Options; 4 System Concept; 5 Backhaul-Energy Model; 6 Results and Discussions; 6.1 Typical Power Consumption of Macro BS and Microwave Backhaul Hub Sites; 6.2 Power Consumption of HetNet and the Break-Even Load; 6.3 Impact of Macro Base Station Load on Power Consumption; 6.4 Energy Savings of Self-Backhauling; 7 Conclusions; References 
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650 0 |a Metaheuristics. 
655 0 |a Electronic books. 
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contents Intro; Preface; Reviewers; GET Authors; Contents; A Theoretical Framework for Big Data Analytics Based on Computational Intelligent Algorithms with the Potential to Reduce Energy Consumption; 1 Introduction; 2 Computational Intelligent Algorithms; 2.1 Characteristics of Computational Intelligent Algorithms; 3 Big Data Analytics and Energy Consumption by Cluster Computing Systems; 3.1 Big Data Analytics Platforms; 3.2 Energy Consumption Over Big Data Platforms; 3.3 Metrics Used for Measuring Power in Big Data Platforms; 4 Computational Intelligent Algorithms and Big Data Analytics, 5 Energy Consumption in the Application of Computational Intelligent Algorithms in Big Data Analytics6 A Proposed Framework for Big Data Analytics Using Computational Intelligent Algorithms; 7 Conclusions; References; Artificial Bee Colony for Minimizing the Energy Consumption in Mobile Ad Hoc Network; 1 Introduction; 2 Energy-Aware Routing Protocol; 3 Routing Protocols in MANET; 3.1 Destination-Sequenced Distance-Vector Routing; 3.2 Ad Hoc On-Demand Distance-Vector Routing Protocol; 4 Artificial Bee Colony for AODV and DSDV; 5 Experimental Results; 5.1 Simulation Settings, 5.2 Performance Metrics5.3 Simulation Results and Performance Comparison; 6 Conclusion; References; A Novel Chicken Swarm Neural Network Model for Crude Oil Price Prediction; 1 Introduction; 2 Artificial Neural Network; 3 Chicken Swarm Optimization; 4 The Proposed Chicken S-NN Algorithm; 5 Results & Discussion; 5.1 Preliminaries; 5.2 Data; 5.3 Discussion; 6 Conclusion; References; Forecasting OPEC Electricity Generation Based on Elman Network Trained by Cuckoo Search Algorithm; 1 Introduction; 2 Elman Network; 3 Cuckoo Search; 4 The Proposed CS Elman Algorithm; 5 Results and Discussion, 5.1 Discussion6 Conclusions; References; Variable Neighborhood Search-Based Symbiotic Organisms Search Algorithm for Energy-Efficient Scheduling of Virtual Machine in Cloud Data Center; 1 Introduction; 2 Related Works; 3 Energy-Efficient Virtual Machine Scheduling Optimization; 3.1 Problem Definition; 3.2 Basic Concepts of Symbiotic Organisms Search; 4 Performance Evaluation; 4.1 Experimental Setup; 4.2 Results and Discussion; 5 Conclusion and Future Work; References; Energy Savings in Heterogeneous Networks with Self-Organizing Backhauling; 1 Introduction, 2 Base Station Types in HETNET and Power System Consideration2.1 Base Station Types in HetNet; 2.2 Power System Consideration of BS Sites; 3 Small Cells Deployment and Backhauling Options; 3.1 Wired Backhaul Options for Small Cells; 3.2 Wireless Backhaul Options; 4 System Concept; 5 Backhaul-Energy Model; 6 Results and Discussions; 6.1 Typical Power Consumption of Macro BS and Microwave Backhaul Hub Sites; 6.2 Power Consumption of HetNet and the Break-Even Load; 6.3 Impact of Macro Base Station Load on Power Consumption; 6.4 Energy Savings of Self-Backhauling; 7 Conclusions; References
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spelling Herawan, Tutut author., Advances on computational intelligence in energy the applications of nature-inspired metaheuristic algorithms in energy Tutut Herawan, Haruna Chiroma and Jemal H. Abawajy, Cham, Switzerland Springer Nature [2019], ©2019, 1 online resource., text rdacontent, computer rdamedia, online resource rdacarrier, Green energy and technology, Includes bibliographical references., Intro; Preface; Reviewers; GET Authors; Contents; A Theoretical Framework for Big Data Analytics Based on Computational Intelligent Algorithms with the Potential to Reduce Energy Consumption; 1 Introduction; 2 Computational Intelligent Algorithms; 2.1 Characteristics of Computational Intelligent Algorithms; 3 Big Data Analytics and Energy Consumption by Cluster Computing Systems; 3.1 Big Data Analytics Platforms; 3.2 Energy Consumption Over Big Data Platforms; 3.3 Metrics Used for Measuring Power in Big Data Platforms; 4 Computational Intelligent Algorithms and Big Data Analytics, 5 Energy Consumption in the Application of Computational Intelligent Algorithms in Big Data Analytics6 A Proposed Framework for Big Data Analytics Using Computational Intelligent Algorithms; 7 Conclusions; References; Artificial Bee Colony for Minimizing the Energy Consumption in Mobile Ad Hoc Network; 1 Introduction; 2 Energy-Aware Routing Protocol; 3 Routing Protocols in MANET; 3.1 Destination-Sequenced Distance-Vector Routing; 3.2 Ad Hoc On-Demand Distance-Vector Routing Protocol; 4 Artificial Bee Colony for AODV and DSDV; 5 Experimental Results; 5.1 Simulation Settings, 5.2 Performance Metrics5.3 Simulation Results and Performance Comparison; 6 Conclusion; References; A Novel Chicken Swarm Neural Network Model for Crude Oil Price Prediction; 1 Introduction; 2 Artificial Neural Network; 3 Chicken Swarm Optimization; 4 The Proposed Chicken S-NN Algorithm; 5 Results & Discussion; 5.1 Preliminaries; 5.2 Data; 5.3 Discussion; 6 Conclusion; References; Forecasting OPEC Electricity Generation Based on Elman Network Trained by Cuckoo Search Algorithm; 1 Introduction; 2 Elman Network; 3 Cuckoo Search; 4 The Proposed CS Elman Algorithm; 5 Results and Discussion, 5.1 Discussion6 Conclusions; References; Variable Neighborhood Search-Based Symbiotic Organisms Search Algorithm for Energy-Efficient Scheduling of Virtual Machine in Cloud Data Center; 1 Introduction; 2 Related Works; 3 Energy-Efficient Virtual Machine Scheduling Optimization; 3.1 Problem Definition; 3.2 Basic Concepts of Symbiotic Organisms Search; 4 Performance Evaluation; 4.1 Experimental Setup; 4.2 Results and Discussion; 5 Conclusion and Future Work; References; Energy Savings in Heterogeneous Networks with Self-Organizing Backhauling; 1 Introduction, 2 Base Station Types in HETNET and Power System Consideration2.1 Base Station Types in HetNet; 2.2 Power System Consideration of BS Sites; 3 Small Cells Deployment and Backhauling Options; 3.1 Wired Backhaul Options for Small Cells; 3.2 Wireless Backhaul Options; 4 System Concept; 5 Backhaul-Energy Model; 6 Results and Discussions; 6.1 Typical Power Consumption of Macro BS and Microwave Backhaul Hub Sites; 6.2 Power Consumption of HetNet and the Break-Even Load; 6.3 Impact of Macro Base Station Load on Power Consumption; 6.4 Energy Savings of Self-Backhauling; 7 Conclusions; References, Online resource; title from PDF title page (EBSCO, viewed July 16, 2019)., Computational intelligence., Metaheuristics., Electronic books., Chiroma, Haruna author., Abawajy, Jemal H. author., Green energy and technology., ELD ebook, LDL ebooks ONIX to marcxml transformation using Record_Load-eBooks_Legal_Deposit_onix2marc_v2-1.xsl 20190722 com.springer.onix.9783319698892 Uk, (OCoLC)1108619455, British Library HMNTS DRT ELD.DS.442388
spellingShingle Herawan, Tutut, Chiroma, Haruna, Abawajy, Jemal H., Advances on computational intelligence in energy: the applications of nature-inspired metaheuristic algorithms in energy, Green energy and technology, Intro; Preface; Reviewers; GET Authors; Contents; A Theoretical Framework for Big Data Analytics Based on Computational Intelligent Algorithms with the Potential to Reduce Energy Consumption; 1 Introduction; 2 Computational Intelligent Algorithms; 2.1 Characteristics of Computational Intelligent Algorithms; 3 Big Data Analytics and Energy Consumption by Cluster Computing Systems; 3.1 Big Data Analytics Platforms; 3.2 Energy Consumption Over Big Data Platforms; 3.3 Metrics Used for Measuring Power in Big Data Platforms; 4 Computational Intelligent Algorithms and Big Data Analytics, 5 Energy Consumption in the Application of Computational Intelligent Algorithms in Big Data Analytics6 A Proposed Framework for Big Data Analytics Using Computational Intelligent Algorithms; 7 Conclusions; References; Artificial Bee Colony for Minimizing the Energy Consumption in Mobile Ad Hoc Network; 1 Introduction; 2 Energy-Aware Routing Protocol; 3 Routing Protocols in MANET; 3.1 Destination-Sequenced Distance-Vector Routing; 3.2 Ad Hoc On-Demand Distance-Vector Routing Protocol; 4 Artificial Bee Colony for AODV and DSDV; 5 Experimental Results; 5.1 Simulation Settings, 5.2 Performance Metrics5.3 Simulation Results and Performance Comparison; 6 Conclusion; References; A Novel Chicken Swarm Neural Network Model for Crude Oil Price Prediction; 1 Introduction; 2 Artificial Neural Network; 3 Chicken Swarm Optimization; 4 The Proposed Chicken S-NN Algorithm; 5 Results & Discussion; 5.1 Preliminaries; 5.2 Data; 5.3 Discussion; 6 Conclusion; References; Forecasting OPEC Electricity Generation Based on Elman Network Trained by Cuckoo Search Algorithm; 1 Introduction; 2 Elman Network; 3 Cuckoo Search; 4 The Proposed CS Elman Algorithm; 5 Results and Discussion, 5.1 Discussion6 Conclusions; References; Variable Neighborhood Search-Based Symbiotic Organisms Search Algorithm for Energy-Efficient Scheduling of Virtual Machine in Cloud Data Center; 1 Introduction; 2 Related Works; 3 Energy-Efficient Virtual Machine Scheduling Optimization; 3.1 Problem Definition; 3.2 Basic Concepts of Symbiotic Organisms Search; 4 Performance Evaluation; 4.1 Experimental Setup; 4.2 Results and Discussion; 5 Conclusion and Future Work; References; Energy Savings in Heterogeneous Networks with Self-Organizing Backhauling; 1 Introduction, 2 Base Station Types in HETNET and Power System Consideration2.1 Base Station Types in HetNet; 2.2 Power System Consideration of BS Sites; 3 Small Cells Deployment and Backhauling Options; 3.1 Wired Backhaul Options for Small Cells; 3.2 Wireless Backhaul Options; 4 System Concept; 5 Backhaul-Energy Model; 6 Results and Discussions; 6.1 Typical Power Consumption of Macro BS and Microwave Backhaul Hub Sites; 6.2 Power Consumption of HetNet and the Break-Even Load; 6.3 Impact of Macro Base Station Load on Power Consumption; 6.4 Energy Savings of Self-Backhauling; 7 Conclusions; References, Computational intelligence., Metaheuristics., Electronic books.
title Advances on computational intelligence in energy: the applications of nature-inspired metaheuristic algorithms in energy
title_auth Advances on computational intelligence in energy the applications of nature-inspired metaheuristic algorithms in energy
title_full Advances on computational intelligence in energy the applications of nature-inspired metaheuristic algorithms in energy Tutut Herawan, Haruna Chiroma and Jemal H. Abawajy
title_fullStr Advances on computational intelligence in energy the applications of nature-inspired metaheuristic algorithms in energy Tutut Herawan, Haruna Chiroma and Jemal H. Abawajy
title_full_unstemmed Advances on computational intelligence in energy the applications of nature-inspired metaheuristic algorithms in energy Tutut Herawan, Haruna Chiroma and Jemal H. Abawajy
title_in_hierarchy Advances on computational intelligence in energy: the applications of nature-inspired metaheuristic algorithms in energy ([2019])
title_short Advances on computational intelligence in energy
title_sort advances on computational intelligence in energy the applications of nature inspired metaheuristic algorithms in energy
title_sub the applications of nature-inspired metaheuristic algorithms in energy
topic Computational intelligence., Metaheuristics., Electronic books.
topic_facet Computational intelligence., Metaheuristics., Electronic books.