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61
Practical Considerations in Frequency Diverse Array Radar Signal Processing
Published 2021Get full text
doctoralThesis -
62
Robustness testing of composed real-time systems
Published 2010“…In this paper, we suggest a methodology for testing robustness of Real-Time Component-Based Systems (RTCBS). A RTCBS system is described as a collection of components where each component is modeled as a Timed Input-Output Automaton (TIOA). …”
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63
Decision-level Gait Fusion for Human Identification at a Distance
Published 2014Get full text
doctoralThesis -
64
An Uncertainty Based Genetic Algorithm Approach for Project Resource Scheduling
Published 2016“…Genetic algorithm was chosen as the main methodology to build resource scheduler. …”
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65
Process Mining over Unordered Event Streams
Published 2020“…While such online algorithms have been proposed for several process mining tasks, from discovery through confor mance checking to time prediction, they all assume that an event stream is ordered, meaning that the order of event generation coincides with their arrival at the analysis engine. …”
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66
A New Parallel Genetic Algorithm Model
Published 2020“…The reduction of the implementation processing time is the basic motivation of genetic algorithms parallelization. …”
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67
A kernelization algorithm for d-Hitting Set
Published 2010“…For a given parameterized problem, π, a kernelization algorithm is a polynomial-time pre-processing procedure that transforms an arbitrary instance of π into an equivalent one whose size depends only on the input parameter(s). …”
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68
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Nonlinear analysis of shell structures using image processing and machine learning
Published 2023“…Hence, obtaining solutions in real-time using direct methods can quickly become computationally overwhelming. …”
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70
Empirical comparison of regression test selection algorithms
Published 2001“…These criteria are: number of selected test cases, execution time, precision, inclusiveness, preprocessing requirements, type of maintenance, level of testing, and type of approach. The empirical results show that the five algorithms can be used for different requirements of regression testing. …”
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Genetic algorithms applications in load frequency control
Published 1995“…A digital simulation is used in conjunction with the genetic algorithm optimization process. The integral of the square of the error and the integral of time-multiplied absolute value of the error performance indices are considered in the search for the optimal AGC parameters. …”
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73
Improvement of Kernel Principal Component Analysis-Based Approach for Nonlinear Process Monitoring by Data Set Size Reduction Using Class Interval
Published 2024“…The proposed algorithm has been tested on three tank system pilot plant and Ain El Kebira Cement rotary kiln process. …”
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74
Parallel Algorithms for Distinguishing Nondeterministic Finite State Machines
Published 2015Get full text
doctoralThesis -
75
Machine Learning Model for a Sustainable Drilling Process
Published 2023Get full text
doctoralThesis -
76
Intelligent Rapidly-Exploring Random Tree Star Algorithm
Published 2024Get full text
doctoralThesis -
77
Multi-Modal Emotion Aware System Based on Fusion of Speech and Brain Information
Published 2019“…This basically follows either a feature-level or decision-level strategy. In all likelihood, while features from several modalities may enhance the classification performance, they might exhibit high dimensionality and make the learning process complex for the most used machine learning algorithms. …”
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78
Recent Advances of Chimp Optimization Algorithm: Variants and Applications
Published 2023“…Chimp Optimization Algorithm (ChOA) is one of the recent metaheuristics swarm intelligence methods. …”
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79
Formal synthesis of VLSI layouts from algorithmic specifications
Published 2020“…In this paper we present a formal approach for high level synthesis. This formal high level syntesis system uses recursive algorithms to model the behaviour to be synthesized. …”
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80
A genetic algorithm for testable data path synthesis
Published 2017“…The approach is formulated as an allocation problem and solved using an efficient genetic algorithm that generates cost-effective testable designs. …”
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