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Record Nr. |
UNISA996395518703316 |
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Titolo |
A full relation or dialogue between a loyallist and a converted phanattick since the time of the late rebellion [[electronic resource] ] : relating their wicked conspiracy, and barbarous intentions, whereby their divellish plots is more fully discovered then ever it was before: gently disputed between them both. Together with the phanaticks lamentation and farewell to that crew. Published as a warning-piece to all the rebellious sectaries |
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Pubbl/distr/stampa |
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[London], : Printed for F. Coles, 1660 |
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Descrizione fisica |
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Soggetti |
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Political satire, English |
Title pages17th cent.England |
Great Britain History Charles II, 1660-1685 Early works to 1800 |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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Place of publication from Wing. |
A fragment; title page only. |
Reproduction of original in the British Library. |
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Sommario/riassunto |
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2. |
Record Nr. |
UNINA9910747590703321 |
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Autore |
Razmjooy Navid |
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Titolo |
Metaheuristics and Optimization in Computer and Electrical Engineering : Volume 2: Hybrid and Improved Algorithms / / edited by Navid Razmjooy, Noradin Ghadimi, Venkatesan Rajinikanth |
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Pubbl/distr/stampa |
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Cham : , : Springer International Publishing : , : Imprint : Springer, , 2023 |
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ISBN |
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Edizione |
[1st ed. 2023.] |
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Descrizione fisica |
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1 online resource (491 pages) |
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Collana |
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Lecture Notes in Electrical Engineering, , 1876-1119 ; ; 1077 |
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Altri autori (Persone) |
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GhadimiNoradin |
RajinikanthVenkatesan |
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Disciplina |
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Soggetti |
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Computational intelligence |
Computational Intelligence |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Nota di contenuto |
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A Comprehensive Survey of Meta-heuristic Algorithms -- Order Reduction of the Time-independent Linear Systems Using the Firefly Algorithm with Neighbourhood Attraction -- Intelligent Voltage Control of Electric Vehicles to Manage Power Quality Problems Using Improved Weed Optimization Algorithm -- Apple Spots and Defects Detection Based on Machine Vision, Fuzzy Systems, and Improved Gray Wolf Optimization Algorithm -- Technical and Economic Evaluation of the Optimal Placement of Fuel Cells in the Distribution System of Petrochemical Industries Based on Improved Firefly Algorithm -- Modeling and Optimal Control of Power System Frequency Load Controller by Applying Disturbance in the System by a Modified Version of Firefly Algorithm -- Design of a System for Melanoma Diagnosis Using Image Processing and Hybrid Optimization Techniques -- Multi-criteria Building Performance Optimization by Mm-based Iaso Method: A Case Study -- A Chameleon Swarm Optimization Model for the Optimal Adjustment of Retrofit Values in Spanish Houses -- Brain Tumor Segmentation Based on Zernike Moments, Enhanced Ant Lion Optimization, and Convolutional Neural Network in Mri Images -- Enhancing Cyber- Physical Resiliency Based on Meta-heuristic |
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Algorithms for Microgrids Against Malicious Attacks -- An Optimized Combination of Spectral and Spatial Features for Hyperspectral Images Classification via Arithmetic Optimization Algorithm -- Multi-objective Optimization Using the Simulation of Net-zero Energy Residential Buildings with the African Vulture Optimizer -- A Systematic Literature Survey in Alzheimer Disease Using Optimization Techniques -- A Survey on Optimization Methods Used for Early Prediction and Diagnosis of Schizophrenia Disorder -- Serially Fused Dual-deep-features Based Chest X-ray Classification Scheme to Detect Tuberculosis -- Chaotic-moth-flame-algorithm Based Scheme to Design Pid Controller for Benchmark Avr. |
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Sommario/riassunto |
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This book discusses different methods of modifying the original metaheuristics and their application in computer and electrical engineering. As the race to develop advanced technology accelerates, a new era of "metaheuristics" has emerged. Through researched-based techniques and collaborative problem-solving, this book helps engineers to find efficient solutions to their engineering challenges. With the help of an expert guide and the collective knowledge of the engineering community, this comprehensive guide shows readers how to use machine learning and other AI techniques to reinvent smart engineering. From understanding the fundamentals to mastering the latest metaheuristics models, this guide provides with the skills and knowledge that need to stay ahead in the technology race. In the previous volume, authors focused on the application of original metaheuristics on electrical and computer sciences. This volume learns how AI and modified metaheuristics can be used to optimize algorithms and create more efficient electrical engineering designs. It gets insights on how data can be effectively processed and discover new techniques for creating sophisticated automation systems. It maximizes the potential of readers’ computer and electrical engineering projects with powerful metaheuristics and optimization techniques. |
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