Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
Results
Showing 1 to 20 of 51 for “"hybrid algorithm"”.
-
Feature selection with a general hybrid algorithm
… the entire set of features. A large number of algorithms have already been proposed for the feature selection problem. Although significantly different with regards to (1) the search strategy they use to determine the right subset of features and (2) how each subset is evaluated, feature …
-
A generalization based hybrid algorithm for clustering semi-structured data
… and data clustering is presented. The algorithm works well on semi-structured data and requires only a minimum of domain knowledge. Since the algorithm reduces the dimensionality of the semi-structured data, clustering of the resulting generalized data often requires less execution time …
-
A hybrid algorithm for the simulation of biochemical reactions and diffusion
… in large quantities. However, no conventional algorithm works well for such a wide range of particle numbers: Small particle numbers require stochastic algorithms, whereas intermediate and large particle numbers can only be treated by computationally more efficient, though perhaps less exact …
-
Multilevel Mesh Adaptivity for Elliptic Boundary Value Problems in two and three Space Dimensions
… implemented and tested a new multilevel hybrid algorithm for the adaptive finite element solution of a general class of variational problems. Our multilevel hybrid algorithm is a combination of node movement, edge swapping and local h-refinement. The adaptive strategy used in our hybrid …
-
Multigrid Algorithms for Massively Parallel Machines
… <em>pde's</em> is the use of the multigrid algorithm. However, the implementation of the multigrid algorithm on massively parallel machines is not very efficient because of (i) low processor utilization and (ii) high communication overheads. These problems need to be addressed to make better …
-
Incorporating the simplicity first methodology into a machine learning genetic algorithm
The classical genetic algorithm provides a powerful yet domain-independent tool for concept learning. However, in general, learning systems based on the genetic algorithm generally do not perform as well as symbolic learning algorithms. Robert Holte's symbolic learning algorithm 1R demonstrated …
-
Towards a New Algorithm for Event Recommendation System
We develop a recommendation algorithm for a local entertainment and ticket provider company. The recommender system predicts the score of items, i.e. event, for each user. The special feature of these events, which makes them very different from similar settings, is that they are perishable: each …
-
Multi-valued Solutions for the Equation of Motion, Darcy-Jordan Model, as a Cauchy Problem: A Shocking Event
… taken in this study is the development of a hybrid algorithm combining the reliability of the Bisection Method and the efficiency of the Secant method. The developed algorithm is coded in MATLAB.</p>
-
Inverse problems in electromagnetics
… media with 72 unknown parameters. The hybrid algorithm combining the differential evolution (DE) algorithm and the simplex method steadily converges to the exact solution. The second inverse problem deals with the detection and the classification of buried metallic objects using …
-
Enhancement of the Fynbos Leaf Optical Recognition Application (FLORA-E)
… research on the use of machine learning algorithms in object identification and classification by designing and developing an artificially intelligent Fynbos Leaf Optical Recognition Application (FLORA) platform. Previous versions of FLORA (versions A through D) were designed to recognise …
-
Playing Tetris with deep reinforcement learning
… The state-of-the-art approach, CBMPI, is a hybrid algorithm based on evolution algorithms and policy iteration. It uses manually crafted features and achieves 51 million lines cleared in an average game. In recent years, deep reinforcement learning (DRL) has achieved outstanding performance …
-
Nondeterminator-3 : a provably good data-race detector that runs in parallel
… based on a provably good parallel SP-maintenance algorithm known as SP-hybrid [2]. For a program with n threads, T1 work, and critical-path length To, the SP-hybrid algorithm runs in O((T1/P + PTO) lg n) expected time when executed on P processors. A data-race detector must also maintain an …
-
Performance evaluation for different intrusion detection system algorithms using machine learning
… the performance of various intrusion detection algorithms based on machine learning. The algorithms considered are the Naive Bays Algorithm, Decision Tree Algorithm and Hybrid Algorithm for different datasets. The evaluation of of various intrusion detection algorithms for different datasets is …
-
Two new approaches for learning Hidden Markov Models
… these hidden variables has been the Baum-Welch algorithm. This thesis utilizes insights from two related fields. The first insight is from Angluin's seminal paper on learning regular sets from queries and counterexamples, which produces a simple and intuitive algorithm that efficiently learns …
-
Methods for Parameter Estimation with Devices in Microgrids
… model structure is established, and a hybrid algorithm for parameter estimation (HAPE) is introduced to estimate defining parameters in the model. In order to verify the load model and the HAPE, two experiments are conducted with different DCPLs using a Power-Hardware-in-the-Loop (PHiL) …
-
Detecting genomic elements of extreme conservation in higher eukaryotes by integration of hash mapping and cache-oblivious in-memory computing
… of these elements. Here, we present a new hybrid approach that integrates the ideas of hash mapping and cache-oblivious in-memory computing. Our algorithm leverages the concept of help-me-help-you, where the data structures are tailored to maximize cache-hit while minimizing cache-miss. As …
-
Particle packings and microstructure modeling of energetic materials
… of particle packings, as well as the methods and algorithms we have developed to generate packings of frictionless hard particles with a computer. We develop two algorithms to model hard-particle systems: a collision-driven molecular dynamics algorithm for the simulation of packings of spheres, …
-
Efficient shadow algorithms on graphics hardware
… This thesis presents two efficient shadow algorithms. Although these algorithms are designed to run in real-time on graphics hardware, they are also well-suited to offline rendering systems. First, we describe a hybrid algorithm for rendering hard shadows accurately and efficiently. Our …
-
Towards Better Turn-Based Strategy Planning Agents: Turn-Based Evolutionary Tree Search
… resulting in state spaces where conventional algorithms like Monte Carlo Tree Search (MCTS) and Rolling Horizon Evolutionary Algorithms (RHEA) struggle to scale. First, we perform an investigation into state-of-the-art Deep Learning based models for game agents in TUBSTAP. Then, we propose …
-
Aspects of generative and discriminative classifiers
… (LLR). Then we studied extensively two hybrid-learning techniques, namely the hybrid generative-discriminative algorithm~\citep{Raina:03} and the generative-discriminative tradeoff (GDT) approach~\citep{Bouchard:04}, for combining the generative and discriminative classifiers. Based on …
Page 1 of 3