بدائل البحث:
correction algorithm » detection algorithm (توسيع البحث), compression algorithms (توسيع البحث), detection algorithms (توسيع البحث)
selection algorithm » detection algorithm (توسيع البحث), detection algorithms (توسيع البحث), prediction algorithms (توسيع البحث)
correction algorithm » detection algorithm (توسيع البحث), compression algorithms (توسيع البحث), detection algorithms (توسيع البحث)
selection algorithm » detection algorithm (توسيع البحث), detection algorithms (توسيع البحث), prediction algorithms (توسيع البحث)
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Using synthetic data to test group-searching algorithms in a context where the correct grouping of species is known and uniquely defined.
منشور في 2024"…(C) We use the synthetic data as input for three families of regression-based algorithms: the EQO of Ref. …"
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Fitting flow of DAKM algorithm.
منشور في 2025"…This paper suggests a better algorithm based on feature points method. During the curve approximation process, the projection points of data points and their parameters are calculated, and the data point parameters are corrected to achieve dynamic adjustment of the knot vector. …"
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GMM-KVS method flowchart.
منشور في 2025"…To address this challenge, this paper proposes a novel trajectory learning method for robotic arms that combines Gaussian Mixture Model with a k-value selection algorithm. The proposed approach leverages the principles of the elbow method along with the properties of exponential functions, correction terms, and weight adjustments to accurately determine the optimal k-value. …"
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Collected demonstration trajectories.
منشور في 2025"…To address this challenge, this paper proposes a novel trajectory learning method for robotic arms that combines Gaussian Mixture Model with a k-value selection algorithm. The proposed approach leverages the principles of the elbow method along with the properties of exponential functions, correction terms, and weight adjustments to accurately determine the optimal k-value. …"
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Schematic diagram of the elbow method.
منشور في 2025"…To address this challenge, this paper proposes a novel trajectory learning method for robotic arms that combines Gaussian Mixture Model with a k-value selection algorithm. The proposed approach leverages the principles of the elbow method along with the properties of exponential functions, correction terms, and weight adjustments to accurately determine the optimal k-value. …"
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