Search Results - (((((((ant OR kkantis) OR wantis) OR hints) OR cantor) OR anne) OR file) OR wanting) algorithms.

Introduction to Mathematical Optimization : From Linear Programming to Metaheuristics. by Yang, Xin-She

Table of Contents: “…Tabu Search""; ""8.1 Tabu Search""; ""8.2 Travelling Salesman Problem""; ""8.3 Tabu Search for TSP""; ""9. Ant Colony Optimization""; ""9.1 Behaviour of Ants""; ""9.2 Ant Colony Optimization""; ""9.3 Double Bridge Problem""; ""9.4 Multi-Peak Functions""; ""10. …”
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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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Understanding Artificial Intelligence. by Sabouret, Nicolas

Table of Contents: “…Small but Strong: Understanding How Ants Find Their Way -- Multi-Agent Systems -- The Algorithm and the Ant -- Just Like in the Ant Colony -- Calculating a Path With Ants -- The More the Merrier! …”
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What intelligence tests miss : the psychology of rational thought by Stanovich, Keith E., 1950-

Table of Contents: “…Inside George W. Bush's mind : hints at what IQ tests miss -- Dysrationalia : separating rationality and intelligence -- The reflective mind, the algorithmic mind, and the autonomous mind -- Cutting intelligence down to size -- Why intelligent people doing foolish things is no surprise -- The cognitive miser : ways to avoid thinking -- Framing and the cognitive miser -- Myside processing : heads I win, tails I win too! …”
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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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Advances in Computational Intelligence : Theory & Applications by Wang, Fei-Yue

Table of Contents: “…Lin and F.-Y. Wang -- 8. Ant colony algorithms: the state-of-the-art / J. …”
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Machine Learning for Mobile : Practical Guide to Building Intelligent Mobile Applications Powered by Machine Learning. by Gopalakrishnan, Revathi

Table of Contents: “…Decision tree Advantages of the decision tree algorithm; Disadvantages of decision trees; Advantages of decision trees; Random forests; Solving the problem using random forest in Core ML; Dataset; Naming the dataset; Technical requirements; Creating the model file using scikit-learn ; Converting the scikit model to the Core ML model; Creating an iOS mobile application using the Core ML model; Summary; Further reading; Chapter 4: TensorFlow Mobile in Android; An introduction to TensorFlow; TensorFlow Lite components; Model-file format; Interpreter; Ops/Kernel…”
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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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Hands-On Artificial Intelligence for IoT : Expert Machine Learning and Deep Learning Techniques for Developing Smarter IoT Systems. by Kapoor, Amita

Table of Contents: “…Using TXT files in PythonCSV format; Working with CSV files with the csv module; Working with CSV files with the pandas module; Working with CSV files with the NumPy module; XLSX format; Using OpenPyXl for XLSX files; Using pandas with XLSX files; Working with the JSON format; Using JSON files with the JSON module; JSON files with the pandas module; HDF5 format; Using HDF5 with PyTables; Using HDF5 with pandas; Using HDF5 with h5py; SQL data; The SQLite database engine; The MySQL database engine; NoSQL data; HDFS; Using hdfs3 with HDFS; Using PyArrow's filesystem interface for HDFS; Summary…”
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Basic data analysis for time series with R by Derryberry, DeWayne R.

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Comprehensive Ruby Programming. by Hudgens, Jordan

Table of Contents: “…-- A better way -- SOLID OOP development -- the Liskov substitution principle -- The LSP definition -- Breaking down the LSP -- The LSP example -- The problem -- The LSP violation -- The fix -- SOLID OOP development -- the interface segregation principle -- The ISP definition -- The ISP code example -- Introducing the moderator -- A better way -- The result -- A caveat -- SOLID OOP development -- the dependency inversion principle -- The DIP in the real world -- The DIP definition -- The DIP code example -- Recap -- Summary -- Chapter 10: Working with the Filesystem in Ruby -- Creating a file -- Ruby File class -- Other options you can pass as the second option -- Reading files into a program using the File class -- Deleting a file -- Appending a file.…”
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Navigation signal processing for GNSS software receivers by Pany, Thomas

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Artificial Intelligence in Semiconductor Industry - Materials to Applications. by Wee, Hui-Ming

Table of Contents: “…Cover -- Guest editorial -- Efficient VLSI architecture for FIR filter design using modified differential evolution ant colony optimization algorithm -- Optimized DA-reconfigurable FIR filters for software defined radio channelizer applications -- Grid -- connected operation and performance of hybrid DG having PV and PEMFC -- High speed data encryption technique with optimized memory based RSA algorithm for communications -- A 10-bit 200 MS/s pipelined ADCwith parallel sampling and switched op-amp sharing technique…”
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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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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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Bio-inspired computation in telecommunications

Table of Contents: “…Bio-inspired optimization algorithms; 1.4.1. SI-Based Algorithms; 1.4.1.1. Ant and bee algorithms; 1.4.1.2. …”
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Modeling Reality : How Computers Mirror Life. by Białynicki-Birula, Iwo

Table of Contents: “…Contents; 1 From building blocks to computers: Models and modeling; 2 The game of life: A legendary cellular automaton; 3 Heads or tails: Probability of an event; 4 Galton's board: Probability and statistics; 5 Twenty questions: Probability and information; 6 Snowflakes: The evolution of dynamical systems; 7 The Lorenz butterfly: Deterministic chaos; 8 From Cantor to Mandelbrot: Self-similarity and fractals; 9 Typing monkeys: Statistical linguistics; 10 The bridges of Königsberg: Graph theory; 11 Prisoner's dilemma: Game theory; 12 Let the best man win: Genetic algorithms.…”
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Optimization of Logistics. by Yalaoui, Alice

Table of Contents: “…2.4.1. Genetic algorithms2.4.2. Ant colonies; 2.4.3. Tabu search; 2.4.4. …”
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The the Python Workshop : a Practical, No-Nonsense Introduction to Python Development. by Bird, Andrew

Table of Contents: “…Table of ContentsVital Python - Math, Strings, Conditionals, and LoopsPython StructuresExecuting Python - Programs, Algorithms, and FunctionsExtending Python, Files, Errors, and GraphsConstructing Python - Classes and MethodsThe Standard LibraryBecoming PythonicSoftware DevelopmentPractical Python - Advanced TopicsData Analytics with pandas and NumPyMachine Learning.…”
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Information technology applications in industry III : selected, peer reviewed papers from the 2014 3rd International Conference on Information Technology and Management Innovation...

Table of Contents: “…A Hybrid Simulate Annealing Algorithm Based on Aircraft Emergency Dispatching SystemA Variable Step-Size BLMS Adaptive Jamming Cancellation Algorithm Based on FFT; Adaptive Extended Kalman Filter for Nonlinear System with Noise Compensating Technology; An Improvement of Apriori Algorithm in Medical Data Mining; An Integrated Algorithm for Low-Carbon City Evaluation Based on Neural Network and Analytic Hierarchy Process; Reliability Optimization for Multi-State Series-Parallel System Design Using Ant Colony Algorithm…”
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