Search Results - (((((((ant OR want) OR semantic) OR find) OR cantor) OR anne) OR share) OR hints) algorithms.

Recent advances in hybrid metaheuristics for dataclustering

Table of Contents: “…Cover -- Title Page -- Copyright -- Contents -- List of Contributors -- Series Preface -- Preface -- Chapter 1 Metaheuristic Algorithms in Fuzzy Clustering -- 1.1 Introduction -- 1.2 Fuzzy Clustering -- 1.2.1 Fuzzy c-means (FCM) clustering -- 1.3 Algorithm -- 1.3.1 Selection of Cluster Centers -- 1.4 Genetic Algorithm -- 1.5 Particle Swarm Optimization -- 1.6 Ant Colony Optimization -- 1.7 Artificial Bee Colony Algorithm -- 1.8 Local Search-Based Metaheuristic Clustering Algorithms -- 1.9 Population-Based Metaheuristic Clustering Algorithms -- 1.9.1 GA-Based Fuzzy Clustering…”
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Evolutionary Computing in Advanced Manufacturing. by Tiwari, Manoj

Table of Contents: “…Cover; Half Title page; Title page; Copyright page; Preface; List of Contributors; Chapter 1: Production Planning Using Genetic Algorithm; 1.1 Introduction; 1.2 Production Planning Models; 1.3 Genetic Algorithm; 1.4 Implementation of GA; 1.5 Summary; Further Reading; Chapter 2: Process Planning through Ant Colony Optimization; 2.1 Introduction; 2.2 Ant Colony Optimization (ACO); References; Chapter 3: Introducing a Hybrid Genetic Algorithm for Integration of Set Up and Process Planning; 3.1 Introduction; 3.2 Process Planning; 3.3 Machine Set-up Time; 3.4 Chromosome Representation.…”
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Parallel computing : technology trends

Table of Contents: “…Feedback-Driven Performance and Precision Tuning for Automatic Fixed Point Exploitation -- Parallel Programming -- A GPU-CUDA Framework for Solving a Two-Dimensional Inverse Anomalous Diffusion Problem -- Parallelization Strategies for GPU-Based Ant Colony Optimization Applied to TSP -- DBCSR: A Blocked Sparse Tensor Algebra Library -- Acceleration of Hydro Poro-Elastic Damage Simulation in a Shared-Memory Environment -- BERTHA and PyBERTHA: State of the Art for Full Four-Component Dirac-Kohn-Sham Calculations -- Prediction-Based Partitions Evaluation Algorithm for Resource Allocation…”
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Handbook of Mathematical Induction. by Gunderson, David S.

Table of Contents: “…Chapter 14: Logic and languageChapter 15: Graphs; Chapter 16: Recursion and algorithms; Chapter 17: Games and recreations; Chapter 18: Relations and functions; Chapter 19: Linear and abstract algebra; Chapter 20: Geometry; Chapter 21: Ramsey theory; Chapter 22: Probability and statistics; Part III: Solutions and hints to exercises; Chapter 23: Solutions: Foundations; Chapter 24: Solutions: Inductive techniques applied to the infinite; Chapter 25: Solutions: Paradoxes and sophisms; Chapter 26: Solutions: Empirical induction; Chapter 27: Solutions: Identities.…”
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Stochastic global optimization : techniques and applications in chemical engineering

Table of Contents: “…Differential evolution : method, developments and chemical engineering applications / Chen Shaoqiang, Gade Pandu Rangaiah and Mekapati Srinivas -- ch. 7. Ant colony optimization : details of algorithms suitable for process engineering / V.K. …”
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Digital journalism, drones, and automation : the language and abstractions behind the news by Dowd, Cate

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Artificial neural systems : principle and practice by Lorrentz, Pierre

Table of Contents: “…INTRODUCTIONDENSITY BASED ALGORITHMS: CLUSTERING ALGORITHMS; NATURE-BASED ALGORITHMS; Evolutionary Algorithm and Programming ; Genetic Algorithm; GA Operators; APPLICATIONS OF GENETIC ALGORITHM; NETWORK METHOD: EDGES AND NODES; MULTI-LAYERED PERCEPTRON; REAL-TIME APPLICATIONS OF STATE-OF-THE-ART ANN SYSTEMS; DEFINITION OF ARTIFICIAL NEURAL NETWORKS (ANN); Intelligence; An Artificial Neural Network (ANN) system; PERFORMANCE MEASURES; Receiver's Operating Characteristics (ROC); Hypothesis Testing; Chi-squared (Goodness-of-fit) Test; CONFLICT OF INTEREST; ACKNOWLEDGEMENTS; REFERENCES…”
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Media smart : lessons, tips and strategies for librarians, classroom instructors and other information professionals by Burkhardt, Joanna M.

Table of Contents: “…Expertise, Authority and Credibility -- Experts -- Sharing information -- Evaluating information -- Authority -- How can authority be evaluated? …”
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Computational models of argument : proceedings of COMMA 2014

Table of Contents: “…Properties of Random VAFs and Implications for Efficient AlgorithmsResolution-Based Grounded Semantics Revisited -- Decomposing Abstract Dialectical Frameworks -- A Principled Approach to the Implementation of Argumentation Models -- Combining Paraconsistent Logic with Argumentation -- Probabilistic Argument Graphs for Argumentation Lotteries -- Enthymeme Construction in Dialogues Using Shared Knowledge -- Strategies in Dialogues: A Game-Theoretic Approach -- Argumentation Logic -- Splitting Abstract Dialectical Frameworks…”
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Generalized Network Design Problems : Modeling and Optimization. by Pop, Petrică C.

Table of Contents: “…3.2 An efficient transformation of the GTSP into the TSP3.3 An exact algorithm for the Generalized Traveling Salesman Problem; 3.4 Integer programming formulations of the GTSP; 3.4.1 Formulations based on the properties of Hamiltonian tours; 3.4.2 Flow based formulations; 3.4.3 A local-global formulation; 3.5 Solving the Generalized Traveling Salesman Problem; 3.5.1 Reinforcing ant colony system for solving the GTSP; 3.5.2 Computational results; 3.5.3 A hybrid heuristic approach for solving the GTSP; 3.5.4 Computational results; 3.6 The drilling problem; 3.6.1 Stigmergy and autonomous robots.…”
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Artificial intelligence with Python : build real-world artificial intelligence applications with Python to intelligently interact with the world around you by Joshi, Prateek

Table of Contents: “…; Clustering data with K-Means algorithm; Estimating the number of clusters with Mean Shift algorithm; Estimating the quality of clustering with silhouette scores; What are Gaussian Mixture Models?…”
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Advanced Analytics with R and Tableau. by Stirrup, Jen

Table of Contents: “…Chapter 6: Advanced Analytics Using ClusteringWhat is Clustering?; Finding clusters in data; Why can't I drag my Clusters to the Analytics pane?…”
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Methods for Network Optimization and Parallel Derivative-free Optimization. by Olsson, Per-Magnus

Table of Contents: “…Intro -- Abstract -- Populärvetenskaplig sammanfattning -- Acknowledgements -- Thesis Introduction -- Contents -- Part I Contributions to Network Optimization -- 1 Introduction -- 2 Related Work -- 3 The Relay Positioning Problems -- 4 Environment Representation and Discretization -- 5 Relay Positioning Algorithms for Single Target Problems -- 6 Relay Positioning for Multiple Targets -- 7 Implementation and Experimental Results -- 8 Discussion -- Bibliography -- Part II Contributions to Derivative-free Optimization -- 9 Introduction -- 10 Setting And Problem Description -- 11 Direct Search Algorithms -- 12 Model Building Algorithms -- 13 Existing Model Building Algorithms -- 14 Radial Basis Functions -- 15 Parallelism in Algorithms for Derivative-Free Optimization -- 16 Information Sharing -- 17 Control of Optimization Algorithms -- 18 Implementation Details -- 19 Testing on Synthetic Test Cases -- 20 Testing On Industrial Test Cases -- 21 Future Work -- 22 Conclusions -- A Terms -- Bibliography.…”
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Navigation signal processing for GNSS software receivers by Pany, Thomas

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Mastering machine learning with scikit-learn : learn to implement and evaluate machine learning solutions with scikit-learn by Hackeling, Gavin

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Machine learning : a Bayesian and optimization perspective by Theodoridis, Sergios, 1951-

Table of Contents: “…Probability and stochastic processes -- Learning in parametric modeling: basic concepts and directions -- Mean-square error linear estimation -- Stochastic gradient descent: the LMS algorithm -- The least-squares family -- Classification: a tour of the classics -- Parameter learning: a convex analytic path -- Sparsity-aware learning: concepts and theoretical foundations -- Sparcity-aware learning: algorithms and applications -- Learning in reproducing Kernel Hilbert spaces -- Bayesian learning: inference and the EM alogrithm -- Bayesian learning: approximate inference and nonparametric models -- Monte Carlo methods -- Probabilistic graphical models: Part I -- Probabilistic graphical models: Part II -- Particle filtering -- Neural networks and deep learning -- Dimensionality reduction -- Appendix A LInear algebra -- Appendix B Probability theory and statistics -- Appendix C Hints on constrained optimization.…”
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Communicating process architectures 2002. by World Occam And Transputer User Group. Technical Meeting (25th: 2002: University Of Reading, U. K.)

Table of Contents: “…Cover; Title page; Contents; Preface; Programme Committee; Papers; Semantics of prialt in Handel-C"! Acceptances, Behaviours and Infinite Activity in CSPP; HCSP: Imperative State and True Concurrency; Consolidating the Agreement Problem Protocol Verification Environment; On the Complexity of Buffer Allocation in Message Passing Systems; Java PastSet -- A Structured Distributed Shared Memory System; Synchronous Active Objects Introduce CSP's Primitives in Java; Configurable Collective Communication in LAM-MPI; Cache-Affinity Scheduling for Fine Grain Multithreading.…”
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Data Analytics Applied to the Mining Industry. by Soofastaei, Ali

Table of Contents: “…Advanced Data Analytics -- Introduction -- Big Data -- Analytics -- Deep Learning -- CNNs -- Deep Neural Network -- Recurrent Neural Network (RNN) -- ML -- Fuzzy Logic -- Classification Techniques -- Clustering -- Evolutionary Techniques -- Genetic Algorithms (GAs) -- Ant Colony Optimization (ACO)…”
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Stairs 2006 : Proceedings of the Third Starting AI Researchers' Symposium

Table of Contents: “…Binarization Algorithms for Approximate Updating in Credal NetsOn Generalizing the AGM Postulates; The Two-Variable Situation Calculus; Base Belief Change and Optimized Recovery; Unsupervised Word Sense Disambiguation Using the WWW; Relational Descriptive Analysis of Gene Expression Data; Solving Fuzzy PERT Using Gradual Real Numbers; Approaches to Efficient Resource-Constrained Project Rescheduling; A Comparison of Web Service Interface Similarity Measures; Finding Alternatives Web Services to Parry Breakdowns; Posters; Smart Ride Seeker Introductory Plan…”
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Python unlocked : become more fluent in Python--learn strategies and techniques for smart and high-performance Python programming by Tigeraniya, Arun

Table of Contents: “…Method resolution orderSuper's superpowers; Using language protocols in classes; Iteration protocol; Context manager protocol; Using abstract classes; Summary; Chapter 3: Functions and Utilities; Defining functions; Decorating callables; Utilities; Summary; Chapter 4: Data Structures and Algorithms; Python built-in data structures; Python library data structures; Third party data structures; Arrays/List; Binary tree; Sorted containers; Trie; Algorithms on scale; Summary; Chapter 5: Elegance with Design Patterns; Observer pattern; Strategy pattern; Singleton pattern; Template pattern.…”
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