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

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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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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Introduction to graph and hypergraph theory by Voloshin, Vitaly I. (Vitaly Ivanovich), 1954-

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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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Artificial intelligence : approaches, tools, and applications

Table of Contents: “…EVOLUTIONARY COMPUTING ; 2.1. Genetic Algorithms ; 2.2. Mechanism of a Genetic Algorithm ; 3. …”
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Essential MATLAB for engineers and scientists by Hahn, Brian D.

Table of Contents: “…MATLAB fundamentals -- Program design and algorithm development -- MATLAB functions data import-export utilities -- Logical vectors -- Matrices of numbers arrays of strings -- Introduction to graphics -- Loops -- Errors and pitfalls -- Function M-files -- Vectors as arrays: advanced data structures -- More graphics -- Graphical User Interfaces (GUIs) -- Dynamics systems -- Simulation -- More matrices -- Introduction to numerical methods -- Toolboxes that come with MATLAB (web chapter).…”
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Metaheuristics for intelligent electrical networks by Héliodore, Frédéric, Nakib, Amir, Ismail, Boussaad, Ouchraa, Salma, Schmitt, Laurent

Table of Contents: “…2.2.1. Genetic algorithms2.2.2. Evolution strategies; 2.2.3. Coevolutionary algorithms; 2.2.4. …”
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MATLAB for Machine Learning. by Ciaburro, Giuseppe

Table of Contents: “…; Data mining and data visualization; Regression analysis; Classification; Cluster analysis; Dimensionality reduction; Neural Network Toolbox; Statistics and algebra in MATLAB; Summary; Chapter 2: Importing and Organizing Data in MATLAB; Familiarizing yourself with the MATLAB desktop; Importing data into MATLAB; The Import Wizard; Importing data programmatically; Loading variables from file; Reading an ASCII-delimited file; Comma-separated value files; Importing spreadsheets.…”
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Analysis of biological data : a soft computing approach

Table of Contents: “…Feature selection for cancer classification using ant colony optimization and support vector machines / A. …”
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Java Deep Learning Projects : Implement 10 Real-World Deep Learning Applications Using Deeplearning4j and Open Source APIs. by Karim, Rezaul

Table of Contents: “…; Artificial Neural Networks; Biological neurons; A brief history of ANNs; How does an ANN learn?; ANNs and the backpropagation algorithm; Forward and backward passes; Weights and biases; Weight optimization; Activation functions.…”
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Implementing cryptography using Python by Bray, Shannon, 1972-

Table of Contents: “…Using Strings -- Introducing Operators -- Understanding Arithmetic Operators -- Understanding Comparison Operators -- Understanding Logical Operators -- Understanding Assignment Operators -- Understanding Bitwise Operators -- Understanding Membership Operators -- Understanding Identity Operators -- Using Conditionals -- Using Loops -- for -- while -- continue -- break -- else -- Using Files -- Understanding Python Semantics -- Sequence Types -- Introducing Custom Functions -- Downloading Files Using Python -- Introducing Python Modules -- Creating a Reverse Cipher -- Summary…”
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Visible Business : Uncover the Blindspots and Engage the World's Female Economy. by Brideson, RJ

Table of Contents: “…Blind Spots; Contents; Foreword; About the Author; Acknowledgements; To my community; To my village; Preface; Introduction; Chapter 1 From history to herstory; The birth of business marketing; Things have changed -- or have they?; Women want more; The wo-man algorithm; Become conscious of the bias; From reject to results; Chapter 2 Are you blind?…”
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Machine learning with R quick start guide : a beginner's guide to implementing machine learning techniques from scratch using R 3.5 by Pastor Sanz, Iván

Table of Contents: “…Accessing components and elements in a listData frames; Accessing elements in data frames; Functions of data frames; Importing or exporting data; Working with functions; Controlling code flow; All about R packages; Installing packages; Necessary packages; Taking further steps; Background on the financial crisis; Summary; Chapter 2: Predicting Failures of Banks -- Data Collection; Collecting financial data; Why FDIC?; Listing files; Finding files; Combining results; Removing tables; Knowing your observations; Handling duplications; Operating our problem; Collecting the target variable…”
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Mastering Scala machine learning by Kozlov, Alexander

Table of Contents: “…Setting up R and SparkRLinux; Mac OS; Windows; Running SparkR via scripts; Running Spark via R's command line; DataFrames; Linear models; Generalized linear model; Reading JSON files in SparkR; Writing Parquet files in SparkR; Invoking Scala from R; Using Rserve; Integrating with Python; Setting up Python; PySpark; Calling Python from Java/Scala; Using sys.process._; Spark pipe; Jython and JSR 223; Summary; Chapter 9: NLP in Scala; Text analysis pipeline; Simple text analysis; MLlib algorithms in Spark; TF-IDF; LDA; Segmentation, annotation, and chunking; POS tagging.…”
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Digital Signal Processing and Applications with the OMAP - L138 EXperimenter. by Reay, Donald S.

Table of Contents: “…1.5.1 Initialization and Configuration File (L138_aic3106_init.c) -- 1.5.2 Header File (L138_aic3106_init.h) -- 1.5.3 Vector Files (vectors_intr.asm and vectors_poll.asm) -- 1.5.4 Linker Command File (linker_dsp.cmd) -- Exercises -- References -- 2. …”
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