Search Results - (((((((want OR wkant) OR mantis) OR wien) OR cantor) OR anne) OR shape) OR hints) algorithms.

Solutions in lidar profiling of the atmosphere by Kovalev, Vladimir A.

Table of Contents: “…1.6.1 Algorithm and Solution Uncertainty1.6.2 Numerical Simulations and Experimental Data; 1.7 Examination of the Remaining Offset in the Backscatter Signal by~Analyzing the Shape of the Integrated Signal; 1.8 Issues in the Examination of the Lidar Overlap Function; 1.8.1 Influence of Distortions in the Lidar Signal when Determining the~Overlap Function; 1.8.2 Issues of Lidar Signal Inversion within the Incomplete Overlap Area; Chapter 2 Essentials and Issues in Separating the Backscatter and Transmission Terms in The Lidar Equation.…”
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Computational intelligence in aerospace sciences

Table of Contents: “…Guenov, Mrco Nunez, Arturo Molina-Cristóbal, Vis Sripawadkul, varun Datta and Atif Riaz ; Surrogate modeling in the service of multidisciplinary design / Stephen Powell and András Sóbester ; Multidisciplinary design optimization of aerospace transportation systems / Edmondo Minisci and Massimilliano Vasile -- Aerodynamics optimization: Aerodynamic shape design using evolutionary computation : a tutorial with examples and case studies / Domenico Quagliarella ; Multiobjective design optimization using Nash games / Jean-Antoine Désidéri and Régis Duvigneau ; Design rule extraction using multiobjective design exploration / Shigeru Obayashi -- Space trajectory design: Automated interplanetary mission planning / Jacob Englander and Bruce Conway ; On the global optimization of multigravity assist trajectories with evolutionary algorithms / Massimilliano Vasile and Edmondo Minisci, Marco Locatelli ; An incremental algorithm for the optimization of multiple gravity assist trajectories / Massimilliano Vasile, Matteo Ceriotti, Victor M. …”
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Mastering Scala machine learning by Kozlov, Alexander

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Parts-feeding systems for assembly : organisation, logistics and automation

Table of Contents: “…A model for kitting operations planningRobust optimization approach to production system with failure in rework and breakdown under uncertainty: evolutionary methods; Re-layout of an assembly area: a case study at Bosch Rexroth Oil Control; A simple mechanical measurement system for the posture evaluation of wing components using the PSO and ICP algorithms; Implementation framework for a fully flexible assembly system (F-FAS); A genetic algorithm for supermarket location problem; New Kanban model for tow-train feeding system design.…”
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3D face modeling, analysis and recognition by Daoudi, Mohamed, Ph. D., Srivastava, Anuj, Veltkamp, Remco C., 1963-

Table of Contents: “…3.5.4 Extension to Facial Surfaces Shape Analysis3.6 The Dense Scalar Field (DSF); 3.7 Statistical Shape Analysis; 3.7.1 Statistics on Manifolds: Karcher Mean; 3.7.2 Learning Statistical Models in Shape Space; 3.8 Applications of Statistical Shape Analysis; 3.8.1 3D Face Restoration; 3.8.2 Hierarchical Organization of Facial Shapes; 3.9 The Iso-geodesic Stripes; 3.9.1 Extraction of Facial Stripes; 3.9.2 Computing Relationships between Facial Stripes; 3.9.3 Face Representation and Matching Using Iso-geodesic Stripes; Exercises; Glossary; References.…”
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Wavelet theory approach to pattern recognition

Table of Contents: “…Comparison with other wavelets. 7.4. Algorithm and experiments -- ch. 8. Skeletonization of ribbon-like shapes with new wavelet function. 8.1. …”
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Numerical Methods for Eigenvalue Problems. by Börm, Steffen

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Insight into Theoretical and Applied Informatics : Introduction to Information Technologies and Computer Science. by Yatsko, Andrzej

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The Finite Element Method : a Practical Course. by Liu, G. R.

Table of Contents: “…3.4.3.3 On other means of construct shape functions3.4.4 Properties of the shape functions; 3.4.5 Formulation of finite element equations in local coordinate system; 3.4.6 Coordinate transformation; 3.4.7 Assembly of global FE equation; 3.4.8 Imposition of displacement constraints; 3.4.9 Solving the global FE equation; 3.5 Static analysis; 3.6 Analysis of free vibration (eigenvalue analysis); 3.7 Transient response; 3.7.1 Central difference algorithm; 3.7.2 Newmark's method (Newmark, 1959); 3.8 Remarks; 3.8.1 Summary of shape function properties.…”
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An introduction to computational engineering with Matlab by Yang, Xin-She

Table of Contents: “…Optimization in Engineering -- 12.1 Introduction -- 12.2 Bioinspired Algorithms -- 12.2.1 Genetic Algorithms -- 12.2.2 Neural Networks…”
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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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Integrated and collaborative product development environment : technologies and implementations by Li, W. D.

Table of Contents: “…Intelligent Optimisation of Process Planning; 5.1 Intelligent Optimisation Strategies for CAPP Systems; 5.2 Knowledge Representation of Process Plans; 5.2.1 Process plan representation; 5.2.2 Machining cost criteria for process plans; 5.2.3 Precedence constraints; 5.3 A Hybrid GA/SA-based Optimisation Method; 5.3.1 Overview of the algorithm; 5.3.2 Genetic algorithm -- phase 1; 5.3.3 Simulated annealing algorithm -- phase 2; 5.3.4 Constraint handling algorithm.…”
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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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Principles of Quantum Computation and Information, Volume I : Basic Concepts. by Casati, Giulio, Strini, Giuliano

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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

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Java Data Mining - Strategy, Standard, and Practice : a Practical Guide for architecture, design, and implementation. by Hornick, Mark F.

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Seismic Data Interpretation using Digital Image Processing by Al-Shuhail, Abdullatif A., Al-Dossary, Saleh A., Mousa, Wail A.

Table of Contents: “…5.5 Two-Dimensional Second-Order Derivative Operator5.5.1 The Coherence Attribute; 5.5.2 The Dip Attribute; 5.6 The Curvature Attribute; 5.7 Curvature of the Surface; 5.7.1 Curve, Velocity, and Curvature; 5.7.2 Surface, Tangent Plane, and Norm; 5.8 Shape Operator, Normal Curvature, and Principal Curvature; 5.8.1 Normal Curvature; 5.8.2 Shape Operator; 5.8.3 The Principal Curvatures; 5.8.4 Calculation of the Principal Curvatures; 5.8.5 Summary of Calculation of Principal Curvature for a Surface; 5.9 The Randomness Attribute; 5.10 Technique for Two-Dimensional Images.…”
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Building Machine Learning Systems with Python. by Richert, Willi

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Ranking the Liveability of the World's Major Cities : the Global Liveable Cities Index (GLCI). by Tan, Khee Giap

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Data clustering in C++ : an object-oriented approach by Gan, Guojun, 1979-

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