Search alternatives:
process optimization » model optimization (Expand Search)
based optimization » whale optimization (Expand Search)
binary base » binary mask (Expand Search), ciliary base (Expand Search), binary image (Expand Search)
can process » a process (Expand Search), carlo process (Expand Search), apar process (Expand Search)
base based » case based (Expand Search), blame based (Expand Search), made based (Expand Search)
process optimization » model optimization (Expand Search)
based optimization » whale optimization (Expand Search)
binary base » binary mask (Expand Search), ciliary base (Expand Search), binary image (Expand Search)
can process » a process (Expand Search), carlo process (Expand Search), apar process (Expand Search)
base based » case based (Expand Search), blame based (Expand Search), made based (Expand Search)
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Feature selection process.
Published 2024“…Motivated by the above, in this proposal, we design an improved model to predict the existence of respiratory disease among patients by incorporating hyperparameter optimization and feature selection. To optimize the parameters of the machine learning algorithms, hyperparameter optimization with a genetic algorithm is proposed and to reduce the size of the feature set, feature selection is performed using binary grey wolf optimization algorithm. …”
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<i>hi</i>PRS algorithm process flow.
Published 2023“…From this dataset we can compute the MI between each interaction and the outcome and <b>(D)</b> obtain a ranked list (<i>I</i><sub><i>δ</i></sub>) based on this metric. <b>(E)</b> Starting from the interaction at the top of <i>I</i><sub><i>δ</i></sub>, <i>hi</i>PRS constructs <i>I</i><sub><i>K</i></sub>, selecting <i>K</i> (where <i>K</i> is user-specified) terms through the greedy optimization of the ratio between MI (<i>relevance</i>) and a suitable measure of similarity for interactions (<i>redundancy)</i> (cf. …”
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Analysis and design of algorithms for the manufacturing process of integrated circuits
Published 2023“…<p>Abstract: The stage of transporting semiconductor chips from the wafer to the support strip is crucial in the integrated circuit manufacturing process. This process can be modeled as a combinatorial optimization problem where the objective is to reduce the total distance the robotic arm must travel to pick up each chip and place it in its corresponding position within the support structure. …”
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MSE for ILSTM algorithm in binary classification.
Published 2023“…In this paper, a novel, and improved version of the Long Short-Term Memory (ILSTM) algorithm was proposed. The ILSTM is based on the novel integration of the chaotic butterfly optimization algorithm (CBOA) and particle swarm optimization (PSO) to improve the accuracy of the LSTM algorithm. …”
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Python-Based Algorithm for Estimating NRTL Model Parameters with UNIFAC Model Simulation Results
Published 2025Subjects: -
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DE algorithm flow.
Published 2025“…<div><p>To solve the problems of insufficient global optimization ability and easy loss of population diversity in building interior layout design, this study proposes a novel layout optimization model integrating interactive genetic algorithm and improved differential evolutionary algorithm to improve the global optimization ability and maintain population diversity in building layout design. …”
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Test results of different algorithms.
Published 2025“…<div><p>To solve the problems of insufficient global optimization ability and easy loss of population diversity in building interior layout design, this study proposes a novel layout optimization model integrating interactive genetic algorithm and improved differential evolutionary algorithm to improve the global optimization ability and maintain population diversity in building layout design. …”
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Algorithm for generating hyperparameter.
Published 2024“…Motivated by the above, in this proposal, we design an improved model to predict the existence of respiratory disease among patients by incorporating hyperparameter optimization and feature selection. To optimize the parameters of the machine learning algorithms, hyperparameter optimization with a genetic algorithm is proposed and to reduce the size of the feature set, feature selection is performed using binary grey wolf optimization algorithm. …”