Search Results - (((((((ant OR mantis) OR anti) OR makart) OR cantor) OR anne) OR share) OR hints) algorithms.

  1. 161

    Optimization advances in electric power systems

    Published 2008
    Table of Contents: “…Unreliability Costs -- 3.5. Proposed Algorithms -- 3.5.1. ES and TS Algorithms -- 3.5.2. …”
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  2. 162

    Integrated and collaborative product development environment : technologies and implementations by Li, W. D.

    Published 2006
    Table of Contents: “…Intelligent Optimisation of Process Planning; 5.1 Intelligent Optimisation Strategies for CAPP Systems; 5.2 Knowledge Representation of Process Plans; 5.2.1 Process plan representation; 5.2.2 Machining cost criteria for process plans; 5.2.3 Precedence constraints; 5.3 A Hybrid GA/SA-based Optimisation Method; 5.3.1 Overview of the algorithm; 5.3.2 Genetic algorithm -- phase 1; 5.3.3 Simulated annealing algorithm -- phase 2; 5.3.4 Constraint handling algorithm.…”
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  3. 163

    Delphi High Performance : Build fast Delphi applications using concurrency, parallel programming and memory management. by Gabrijelčič, Primož

    Published 2018
    Table of Contents: “…; Different types of speed; Algorithm complexity; Big O and Delphi data structures; Data structures in practice; Mr. …”
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  4. 164

    Big Data and HPC. by Grandinetti, L.

    Published 2018
    Table of Contents: “…Reliability-Aware Voltage Scaling of Multicore Processors in Dark Silicon EraTime Collection: An Abstraction for Shared Objects in Parallel Programming; Parallel and Distributed Analysis of Microarray Data; Extracting Distributed Architecture from Source Code Using an Evolutionary Approach; An Architectural Approach to Grid Provisioning; Subject Index; Author Index.…”
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  5. 165

    Artificial intelligence for big data : complete guide to automating big data solutions using artificial intelligence techniques. by Deshpande, Anand

    Published 2018
    Table of Contents: “…Snowball stemming -- Lancaster stemming -- Lovins stemming -- Dawson stemming -- Lemmatization -- N-grams -- Feature extraction -- One hot encoding -- TF-IDF -- CountVectorizer -- Word2Vec -- CBOW -- Skip-Gram model -- Applying NLP techniques -- Text classification -- Introduction to Naive Bayes' algorithm -- Random Forest -- Naive Bayes' text classification code example -- Implementing sentiment analysis -- Frequently asked questions -- Summary -- Chapter 7: Fuzzy Systems -- Fuzzy logic fundamentals -- Fuzzy sets and membership functions -- Attributes and notations of crisp sets -- Operations on crisp sets -- Properties of crisp sets -- Fuzzification -- Defuzzification -- Defuzzification methods -- Fuzzy inference -- ANFIS network -- Adaptive network -- ANFIS architecture and hybrid learning algorithm -- Fuzzy C-means clustering -- NEFCLASS -- Frequently asked questions -- Summary -- Chapter 8: Genetic Programming -- Genetic algorithms structure -- KEEL framework -- Encog machine learning framework -- Encog development environment setup -- Encog API structure -- Introduction to the Weka framework -- Weka Explorer features -- Preprocess -- Classify -- Attribute search with genetic algorithms in Weka -- Frequently asked questions -- Summary -- Chapter 9: Swarm Intelligence -- Swarm intelligence -- Self-organization -- Stigmergy -- Division of labor -- Advantages of collective intelligent systems -- Design principles for developing SI systems -- The particle swarm optimization model -- PSO implementation considerations -- Ant colony optimization model -- MASON Library -- MASON Layered Architecture -- Opt4J library -- Applications in big data analytics -- Handling dynamical data -- Multi-objective optimization -- Frequently asked questions -- Summary -- Chapter 10: Reinforcement Learning -- Reinforcement learning algorithms concept.…”
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  6. 166

    CUDA programming : a developer's guide to parallel computing with GPUs by Cook, Shane

    Published 2013
    Table of Contents: “…ALGORITHMIC ISSUESFINDING AND AVOIDING ERRORS; DEVELOPING FOR FUTURE GPUS; FURTHER RESOURCES; CONCLUSION; References; Index.…”
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  7. 167

    Handbook for pandemic and mass-casualty planning and response

    Published 2012
    Table of Contents: “…Burn Injuries during Mass-Casualty IncidentsBlast Injuries; Section 3: Communication and Information Sharing; Information Sharing in Practice and for Practice: Mass-Casualty Cases; Communication between Emergency Medical Services and Media during Mass-Casualty Events in Croatia; Just-in-Time Information; Collaboration Topologies for Interdisciplinary and Interlevel Information Exchange; Networks and Their Role in Counteracting Contemporary Global Threats: A New Model; Architecture of R & D Project Management Systems at Medical Institutions; Lessons Learned; Lessons Learned; Subject Index…”
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  8. 168

    AI and human thought and emotion by Freed, Sam (Philosophy professor)

    Published 2020
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  9. 169

    High performance computing on complex environments by Jeannot, Emmanuel

    Published 2014
    Table of Contents: “…Chapter 4: Parallel Algorithms for Parabolic Problems on Graphs in Neuroscience4.1 Introduction; 4.2 Formulation of the Discrete Model; 4.3 Parallel Algorithms; 4.4 Computational Results; 4.5 Conclusions; Acknowledgments; References; Part III: Communication and Storage Considerations in High-Performance Computing; Chapter 5: An Overview of Topology Mapping Algorithms and Techniques in High-Performance Computing; 5.1 Introduction; 5.2 General Overview; 5.3 Formalization of the Problem; 5.4 Algorithmic Strategies for Topology Mapping; 5.5 Mapping Enforcement Techniques; 5.6 Survey of Solutions.…”
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  10. 170

    Materials Science and Intelligent Technologies Applications : Selected, Peer Reviewed Papers from the 2014 3rd International Conference on Key Engineering Materials and Computer Sc...

    Published 2014
    Table of Contents: “…Automatic Badminton Action Recognition Using RGB-D SensorKinect-Based Badminton Action Analysis System; A Review of Hot Topic Detection and Tracking Technology; Study on the Improvement of TFIDF Algorithm in Data Mining; A New Protocol for Secure Distributed Multiplication of Two Polynomial Shared Values; Human Posture Recognition Based on DAG-SVMS; The Design and Implementation of Astronomical Multi-Catalog Storage and Cross-Match Based on Hadoop; The Multi-Scale Hough Transform Lane Detection Method Based on the Algorithm of Otsu and Canny; Design of Heart Sound Analyzer.…”
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  11. 171
  12. 172

    Parallel Computing : Advances and Current Issues, Proceedings of the International Conference Parco2001. by Joubert, G. R.

    Published 2002
    Table of Contents: “…Committees ; Preface ; Invited Papers ; Deploying Parallel Numerical Library Routines to Cluster Computing in a Self Adapting Fashion ; 1 Overview ; 2 Numerical libraries in shared homogeneous distributed environments ; 3 Sample software implementation and results.…”
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  13. 173
  14. 174

    Advances in time series forecasting. Volume 2

    Published 2017
    Table of Contents: “…INTRODUCTION -- CLASSICAL TIME SERIES FORECASTING MODELS -- ARTIFICIAL NEURAL NETWORKS FOR FORECASTING TIME SERIES -- A NEW ARTIFICIAL NEURAL NETWORK WITH DETERMINISTIC COMPONENTS -- APPLICATIONS -- CONCLUSION -- CONFLICT OF INTEREST -- ACKNOWLEDGEMENTS -- REFERENCES -- A Fuzzy Time Series Approach Based on Genetic Algorithm with Single Analysis Process -- Ozge Cagcag Yolcu* -- INTRODUCTION -- FUZZY TIME SERIES -- RELATED METHODS -- Genetic Algorithm (GA) -- Single Multiplicative Neuron Model -- PROPOSED METHOD -- APPLICATIONS -- CONCLUSION AND DISCUSSION -- CONFLICT OF INTEREST -- ACKNOWLEDGEMENTS -- REFERENCES -- Forecasting Stock Exchanges with Fuzzy Time Series Approach Based on Markov Chain Transition Matrix -- Cagdas Hakan Aladag1,* and Hilal Guney2 -- INTRODUCTION -- FUZZY TIME SERIES -- TSAUR 'S FUZZY TIME SERIES MARKOV CHAIN MODEL -- THE IMPLEMENTATION -- CONCLUSION -- CONFLICT OF INTEREST -- ACKNOWLEDGEMENTS -- REFERENCES -- A New High Order Multivariate Fuzzy Time Series Forecasting Model -- Ufuk Yolcu* -- INTRODUCTION -- RELATED METHODOLOGY -- The Fuzzy C-Means (FCM) Clustering Method -- Single Multiplicative Neuron Model Artificial Neural Network (SMN-ANN) -- Fuzzy Time Series -- THE PROPOSED METHOD -- APPLICATIONS -- CONCLUSIONS AND DISCUSSION -- CONFLICT OF INTEREST -- ACKNOWLEDGEMENTS -- REFERENCES -- Fuzzy Functions Approach for Time Series Forecasting -- Ali Z. …”
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  15. 175

    Process control : a practical approach by King, Myke, 1951-

    Published 2016
    Table of Contents: “…Title Page ; Copyright Page; Contents; Preface; About the Author; Chapter 1 Introduction; Chapter 2 Process Dynamics; 2.1 Definition; 2.2 Cascade Control; 2.3 Model Identification; 2.4 Integrating Processes; 2.5 Other Types of Process; 2.6 Robustness; Chapter 3 PID Algorithm; 3.1 Definitions; 3.2 Proportional Action; 3.3 Integral Action; 3.4 Derivative Action; 3.5 Versions of Control Algorithm; 3.6 Interactive PID Controller; 3.7 Proportional-on-PV Controller ; 3.8 Nonstandard Algorithms; 3.9 Tuning; 3.10 Ziegler-Nichols Tuning Method ; 3.11 Cohen-Coon Tuning Method.…”
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  16. 176

    Scientific computing with multicore and accelerators

    Published 2010
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  17. 177

    Stochastic Models in Reliability Engineering. by Cui, Lirong

    Published 2020
    Table of Contents: “…4.3.1 Run and Phrase -- 4.3.2 Multi-State Compression Algorithm -- 4.4 Proposed Multi-State Inference Algorithm -- 4.4.1 Rules for Calculating Intermediate Variables -- 4.4.2 Proposed Multi-State Inference Algorithm -- 4.5 Case Study -- 4.5.1 Case Background -- 4.5.2 Calculation and Analysis -- 4.6 Summary -- Appendix A -- Appendix B -- References -- Chapter 5 Reliability Analysis of Demand-Based Warm Standby System with Multi-State Common Bus -- 5.1 Introduction -- 5.2 Model Description for a DBWSS with Multi-State Common Bus Performance Sharing…”
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  18. 178

    PRINCIPLES OF QUANTUM ARTIFICIAL INTELLIGENCE. by Wichert, Andreas

    Published 2013
    Table of Contents: “…Computation; 2.1 Entscheidungsproblem; 2.1.1 Cantor's diagonal argument; 2.1.2 Reductio ad absurdum; 2.2 Complexity Theory; 2.2.1 Decision problems; 2.2.2 P and NP; 2.3 Church-Turing Thesis; 2.3.1 Church-Turing-Deutsch principle; 2.4 Computers; 2.4.1 Analog computers; 2.4.2 Digital computers; 2.4.3 Von Neumann architecture; 3. …”
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  19. 179

    Hands-On Blockchain with Hyperledger : Building Decentralized Applications with Hyperledger Fabric and Composer. by Baset, Salman

    Published 2018
    Table of Contents: “…Decentralization with systemic governanceEnterprise support; Use case-driven pluggability choices; Shared ledger technology; Consensus; Crypto algorithms and encryption technology; Use case-driven pluggable choices; Enterprise integration and designing for extensibility; Other considerations; Consensus, ACID property, and CAP; CAP; ACID; Attestation -- SSCs are signed and encrypted; Use of HSMs; Summary; Chapter 2: Exploring Hyperledger Fabric; Building on the foundations of open computing; Fundamentals of the Hyperledger project; The Linux Foundation ; Hyperledger.…”
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  20. 180

    Cognitive Electronic Warfare : An Artificial Intelligence Approach. by Haigh, Karen

    Published 2021
    Table of Contents: “…-- 1.5 Reader's Guide -- 1.6 Conclusion -- References -- 2 Objective Function -- 2.1 Observables That Describe the Environment -- 2.1.1 Clustering Environments -- 2.2 Control Parameters to Change Behavior -- 2.3 Metrics to Evaluate Performance -- 2.4 Creating a Utility Function -- 2.5 Utility Function Design Considerations -- 2.6 Conclusion -- References -- 3 ML Primer -- 3.1 Common ML Algorithms -- 3.1.1 SVMs -- 3.1.2 ANNs -- 3.2 Ensemble Methods -- 3.3 Hybrid ML -- 3.4 Open-Set Classification -- 3.5 Generalization and Meta-learning -- 3.6 Algorithmic Trade-Offs -- 3.7 Conclusion -- References -- 4 Electronic Support -- 4.1 Emitter Classification and Characterization -- 4.1.1 Feature Engineering and Behavior Characterization -- 4.1.2 Waveform Classification -- 4.1.3 SEI -- 4.2 Performance Estimation -- 4.3 Multi-Intelligence Data Fusion -- 4.3.1 Data Fusion Approaches -- 4.3.2 Example: 5G Multi-INT Data Fusion for Localization -- 4.3.3 Distributed-Data Fusion -- 4.4 Anomaly Detection -- 4.5 Causal Relationships -- 4.6 Intent Recognition -- 4.6.1 Automatic Target Recognition and Tracking -- 4.7 Conclusion -- References -- 5 EP and EA -- 5.1 Optimization -- 5.1.1 Multi-Objective Optimization -- 5.1.2 Searching Through the Performance Landscape -- 5.1.3 Optimization Metalearning -- 5.2 Scheduling -- 5.3 Anytime Algorithms -- 5.4 Distributed Optimization -- 5.5 Conclusion.…”
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