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processing algorithm » processing algorithms (Expand Search)
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fusion algorithm » auction algorithm (Expand Search), cosine algorithm (Expand Search)
time processing » image processing (Expand Search), text processing (Expand Search)
processing algorithm » processing algorithms (Expand Search)
method algorithm » mould algorithm (Expand Search)
fusion algorithm » auction algorithm (Expand Search), cosine algorithm (Expand Search)
time processing » image processing (Expand Search), text processing (Expand Search)
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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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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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Parallel Algorithms for Distinguishing Nondeterministic Finite State Machines
Published 2015Get full text
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Machine Learning Model for a Sustainable Drilling Process
Published 2023Get full text
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Block constrained pressure residual preconditioning for two-phase flow in porous media by mixed hybrid finite elements
Published 2023“…<p dir="ltr">This work proposes an original preconditioner that couples the Constrained Pressure Residual (CPR) method with block preconditioning for the efficient solution of the linearized systems of equations arising from fully implicit multiphase flow models. …”
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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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A hybrid graph representation for exact graph algorithms
Published 2014“…We investigate practical implementation-based aspects of exact graph algorithms by providing a simple hybrid graph representation that trades space for time to address the said take-back challenge. …”
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Learning control algorithms for tracking "slowly" varying trajectories
Published 1997“…This is due to the requirement that all learning algorithms assume that a desired output is given a priori over the time duration t /spl isin/ ~0,T\. …”
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A Parallel Neural Networks Algorithm for the Clique Partitioning Problem
Published 2002“…The proposed algorithm has a time complexity of O(1) for a neural network with n vertices and c cliques. …”
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Real-Time Smart-Digital Stethoscope System for Heart Diseases Monitoring
Published 2019“…The cost-adjusted optimized ensemble algorithm can produce 97% and 88% accuracy of classifying abnormal and normal HS, respectively.…”
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Burst Round Robin as a Proportional-Share Scheduling Algorithm
Published 2020“…Experiments on the implemented simulator showed that quickly knocking away shortest processes achieves better turnaround time, waiting time, and response time. …”
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A Parallel Algorithm for Inverse Halftoning and its Hardware Implementation
Published 2020“…This paper proposes a parallel algorithm for inverse halftoning by parallelizing the LUT method of inverse halftoning. …”
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Reinforcement R-learning model for time scheduling of on-demand fog placement
Published 2020“…We also demonstrate the ability of our model to improve over time by adapting the new demand of users. Experiments comparing the decisions of our model with two other potential fog placement approaches used for task/service scheduling (threshold based and random based) show that the number of processed requests performed by the cloud decreases from 100 to 30% with a limited number of fogs to push. …”
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The buffered work-pool approach for search-tree based optimization algorithms
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Evolutionary algorithms for state justification in sequential automatic test pattern generation
Published 2005“…A common search operation in sequential Automatic Test Pattern Generation is to justify a desired state assignment on the sequential elements. State justification using deterministic algorithms is a difficult problem and is prone to many backtracks, which can lead to high execution times. …”
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Stochastic P-type/D-type iterative learning control algorithms
Published 2003“…This paper presents stochastic algorithms that compute optimal and sub-optimal learning gains for a P-type iterative learning control algorithm (ILC) for a class of discrete-time-varying linear systems. …”
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