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

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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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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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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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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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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Integration of swarm intelligence and artificial neural network

Table of Contents: “…Dehuri -- Coherent biclusters of microarray data by imitating the ecosystem : an ant colony algorithmic approach / D. Mishra, A.K. …”
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Intelligent Technologies : From Theory to Applications - The New Trends in Computational Intelligence. by Kvasnicka, V.

Table of Contents: “…Neural Networks; Superconvergence Concept in Machine Learning; Application of the Parallel Population Learning Algorithm to Training Feed-forward ANN; Markovian Architectural Bias of Recurrent Neural Networks; SOFM Training Speedup; Generalized Forecasting Sigma-Pi Neural Network; Human Centered Intelligent Robots Using "Ontological Neural Network"; Trajectory Bounds of Solutions of Delayed Cellular Neural Networks Differential Systems; From Plain to Modular Topology: Automatic Modularization of Structured ANNs.…”
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TensorFlow Reinforcement Learning Quick Start Guide : Get up and Running with Training and Deploying Intelligent, Self-Learning Agents Using Python. by Balakrishnan, Kaushik

Table of Contents: “…Learning the theory behind a DQNUnderstanding target networks; Learning about replay buffer; Getting introduced to the Atari environment; Summary of Atari games; Pong; Breakout; Space Invaders; LunarLander; The Arcade Learning Environment ; Coding a DQN in TensorFlow; Using the model.py file; Using the funcs.py file; Using the dqn.py file; Evaluating the performance of the DQN on Atari Breakout; Summary; Questions; Further reading; Chapter 4: Double DQN, Dueling Architectures, and Rainbow; Technical requirements; Understanding Double DQN ; Coding DDQN and training to play Atari Breakout…”
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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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