Search Results - (((((((ant OR kkantis) OR wantis) OR hints) OR cantor) OR anne) OR fine) OR granting) algorithms.

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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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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OIPE 2012

Table of Contents: “…N-level output space mapping for electromagnetic design optimizationHigh-speed functionality optimization of five-phase PM machine using third harmonic current; Topology optimization of magnetostatic shielding using multistep evolutionary algorithms with additional searches in a restricted design space ; Adaptive unscented transform for uncertainty quantification in EMC large-scale systems; Ant colony optimization for the topological design of interior permanent magnet (IPM)machines; Multiobjective approach developed for optimizing the dynamic behavior of incremental linear actuators.…”
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Data Analytics in Bioinformatics : A Machine Learning Perspective. by Satpathy, Rabinarayan

Table of Contents: “…3.4.1 Comparative Analysis of ANN With Broadly Used Traditional ML Algorithms -- 3.5 Critical Analysis -- 3.6 Conclusion -- References -- Part 2: MACHINE LEARNING AND GENOMIC TECHNOLOGY, FEATURE SELECTION AND DIMENSIONALITY REDUCTION -- 4 Dimensionality Reduction Techniques: Principles, Benefits, and Limitations -- 4.1 Introduction -- 4.2 The Benefits and Limitations of Dimension Reduction Methods -- 4.3 Components of Dimension Reduction -- 4.3.1 Feature Selection -- 4.3.2 Feature Reduction -- 4.4 Methods of Dimensionality Reduction -- 4.4.1 Principal Component Analysis (PCA)…”
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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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Design of Ultra Wideband Power Transfer Networks : Real Frequency Techniques and Road Maps for Practical Designs. by Yarman, Binboga Siddik

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Practical breast pathology by Tot, Tibor, Tabár, László, Dean, Peter B.

Table of Contents: “…The Most Common Benign Breast Lesions and their Borderline and Malignant Counterparts; 7. Fine-Needle Aspiration or Core Biopsy: A Preoperative Diagnostic Algorithm; 8. …”
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Agent-based computing

Table of Contents: “…Analysis of Algorithm -- 2.1.1. Chain-Like Agent Structure -- 2.1.2. …”
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Advances in Knowledge-Based and Intelligent Engineering and Information Systems by Frydman, Claudia

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Fundamentals of patenting and licensing for scientists and engineers by Ma, Matthew Y.

Table of Contents: “…Patenting beyond core algorithms. 5.4. Innovation harvesting. 5.5. Patent landscaping. 5.6. …”
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Delphi High Performance : Build fast Delphi applications using concurrency, parallel programming and memory management. by Gabrijelčič, Primož

Table of Contents: “…Object file formatsObject file linking in practice; Using C++ libraries; Using a proxy DLL in Delphi; Summary; Chapter 9: Best Practices; About performance; Fixing the algorithm; Fine-tuning the code; Memory management; Getting started with the parallel world; Working with parallel tools; Exploring parallel practices; Using external libraries; Final words; Other Books You May Enjoy; Index.…”
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Future Farming. by Shukla, Praveen Kumar

Table of Contents: “…PROPOSED METHODOLOGY -- Pre-processing -- Leaf Image from Plants -- Segmentation Model Using Improved Canny Algorithm -- Steps of Improved Canny Algorithm -- Leaf Image Feature Selection Using Hybrid Black Widow Optimization Algorithm with Mayfly Optimization Algorithm (BWO-MA) -- Pseudo-Code of the Hybrid (BWO-MA) Algorithm -- Output: Objective Function's -RMSE -- Leaf Image Classification Using (BWO-MA) with ANN -- Hyper-Parameter Tuning With (BWO-MA) -- RESULT AND DISCUSSION -- Dataset Description -- Evaluation & Results -- CONCLUSION -- REFERENCES…”
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Rough fuzzy image analysis : foundations and methodologies

Table of Contents: “…1. Cantor, fuzzy, near, and rough sets in image analysis / James F. …”
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Differential algebra and related topics - proceedings of the international workshop. by SIT, WILLIAM Y.

Table of Contents: “…6 Reduction Algorithms 7 Rosenfeld Properties of an Autoreduced Set ; 8 Coherence and Rosenfeld's Lemma ; 9 Ritt-Raudenbush Basis Theorem ; 10 Decomposition Problems ; 11 Component Theorems ; 12 The Low Power Theorem ; Appendix: Solutions and hints to selected exercises ; References…”
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An investigation of microRNA target regulation mechanisms using an integrative approach by Schmitz, Ulf

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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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Deep Learning with TensorFlow : Explore neural networks and build intelligent systems with Python, 2nd Edition. by Zaccone, Giancarlo

Table of Contents: “…; Artificial neural networks; The biological neurons; The artificial neuron; How does an ANN learn?; ANNs and the backpropagation algorithm; Weight optimization; Stochastic gradient descent; Neural network architectures; Deep Neural Networks (DNNs); Multilayer perceptron; Deep Belief Networks (DBNs).…”
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Visual Data Mining : The VisMiner Approach. by Anderson, Russell K.

Table of Contents: “…Regression Analysis -- The Regression Model -- Correlation and Causation -- Algorithms for Regression Analysis -- Assessing Regression Model Performance -- Model Validity -- Looking Beyond R2 -- Polynomial Regression -- Artificial Neural Networks for Regression Analysis -- Dataset Preparation -- Tutorial -- A Regression Model for Home Appraisal -- Modeling with the Right Set of Observations -- Exercise 6.1 -- ANN Modeling -- The Advantage of ANN Regression -- Top-Down Attribute Selection -- Issues in Model Interpretation -- Model Validation -- Model Application -- Summary…”
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DSP with Python Programming. by Charbit, Maurice

Table of Contents: “…Gaussian linear case: Kalman algorithm; 3.5. Discrete finite Markov case; 4 Monte-Carlo Methods; 4.1. …”
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