Parallel genetic algorithms for financial pattern discovery using GPUs. (2018)

• Record Type: Book
• Further Information: Note: João Baúto, Rui Neves, Nuno Horta.
• Authors: Baúto, João; Neves, Rui César das; Horta, Nuno C. G
• Contents: Intro; Preface; Contents; Acronyms; 1 Introduction; 1.1 Motivation; 1.2 Goals; 1.3 Book Outline; References; 2 Background; 2.1 Time Series Analysis; 2.1.1 Euclidean Distance; 2.1.2 Dynamic Time Warping; 2.1.3 Piecewise Linear Approximation; 2.1.4 Piecewise Aggregate Approximation; 2.1.5 Symbolic Aggregate approXimation; 2.2 Genetic Algorithm; 2.2.1 Selection Operator; 2.2.2 Crossover Operator; 2.2.3 Mutation Operator; 2.3 Graphics Processing Units; 2.3.1 NVIDIA's GPU Architecture Overview; 2.3.2 NVIDIA's GPU Architectures; 2.3.3 CUDA Architecture; 2.4 Conclusions; References 3 State-of-the-Art in Pattern Recognition Techniques3.1 Middle Curve Piecewise Linear Approximation; 3.2 Perceptually Important Points; 3.3 Turning Points; 3.4 Symbolic Aggregate approXimation; 3.5 Shapelets; 3.6 Conclusions; References; 4 SAX/GA CPU Approach; 4.1 SAX/GA CPU Approach; 4.1.1 Population Generation; 4.1.2 Fitness Evaluation; 4.1.3 Population Selection; 4.1.4 Chromosome Crossover; 4.1.5 Individual Mutation; 4.2 SAX/GA Performance Analysis; 4.3 Conclusions; References; 5 GPU-Accelerated SAX/GA; 5.1 Parallel SAX Representation; 5.1.1 Prototype 1: SAX Transformation On-Demand 5.1.2 Prototype 2: Speculative FSM5.1.3 Solution A: SAX/GA with Speculative GPU SAX Transformation; 5.2 Parallel Dataset Training; 5.2.1 Prototype 3: Parallel SAX/GA Training; 5.2.2 Solution B: Parallel SAX/GA Training with GPU Fitness Evaluation; 5.3 Fully GPU-Accelerated SAX/GA; 5.3.1 Population Generation Kernel; 5.3.2 Population Selection; 5.3.3 Gene Crossover Kernel; 5.3.4 Gene Mutation Kernel; 5.3.5 Execution Flow; 5.4 Conclusions; Reference; 6 Results; 6.1 SAX/GA Initial Constraints; 6.2 Study Case A: Execution Time; 6.2.1 Solution A: SAX/GA with Speculative FSM 6.2.2 Solution B: Parallel Dataset Training6.2.3 Solution C: Fully GPU-Accelerated SAX/GA; 6.3 Study Case B: FSM Prediction Rate; 6.4 Study Case C: Quality of Solutions; 6.5 Conclusions; 7 Conclusions and Future Work; 7.1 Future Work
• Publisher Details: Cham, Switzerland : Springer
• Publication Date: 2018
• Extent: 1 online resource (xiv, 91 pages), illustrations
• Subjects: 006.3/823; Engineering; Genetic algorithms; Parallel processing (Electronic computers); Pattern recognition systems; COMPUTERS / General; Genetic algorithms; Parallel processing (Electronic computers); Pattern recognition systems; Mathematics -- Applied; Finance; Finance & accounting; Financial engineering; Finance; Computers -- Intelligence (AI) & Semantics; Artificial intelligence; Electronic books
• Languages: English
• ISBNs: 9783319733296
• Related ISBNs: 331973329X; 9783319733289; 3319733281
• Notes: Note: Includes bibliographical references.; Note: Online resource; title from PDF title page (SpringerLink, viewed February 6, 2018).
• Access Rights: Legal Deposit; Only available on premises controlled by the deposit library and to one user at any one time; The Legal Deposit Libraries (Non-Print Works) Regulations (UK).
• Access Usage: Restricted: Printing from this resource is governed by The Legal Deposit Libraries (Non-Print Works) Regulations (UK) and UK copyright law currently in force.