بدائل البحث:
algorithm python » algorithm within (توسيع البحث), algorithms within (توسيع البحث)
algorithm heart » algorithm where (توسيع البحث), algorithm lennard (توسيع البحث), algorithm reality (توسيع البحث)
algorithm both » algorithm blood (توسيع البحث), algorithm b (توسيع البحث), algorithm etc (توسيع البحث)
heart function » graft function (توسيع البحث)
algorithm python » algorithm within (توسيع البحث), algorithms within (توسيع البحث)
algorithm heart » algorithm where (توسيع البحث), algorithm lennard (توسيع البحث), algorithm reality (توسيع البحث)
algorithm both » algorithm blood (توسيع البحث), algorithm b (توسيع البحث), algorithm etc (توسيع البحث)
heart function » graft function (توسيع البحث)
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Comparison of different algorithms.
منشور في 2025"…A sophisticated optimization model has been developed to simulate the optimal operation of machinery, aiming to maximize equipment utilization efficiency while addressing the challenges posed by worker fatigue. An innovative algorithm, the improved hybrid gray wolf and whale algorithm fused with a penalty function for construction machinery optimization (IHWGWO), is introduced, incorporating a penalty function to handle constraints effectively. …"
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Table 1_Establishment of reliable identification algorithms for acute heart failure or acute exacerbation of chronic heart failure using clinical data from a medical information da...
منشور في 2025"…Introduction<p>This study aimed to evaluate the validity of algorithms based on electronic health data in identifying cases of acute heart failure and acute exacerbation of chronic heart failure at multiple institutions using the Medical Information Database Network (MID-NET®) in Japan.…"
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ADT: A Generalized Algorithm and Program for Beyond Born–Oppenheimer Equations of “<i>N</i>” Dimensional Sub-Hilbert Space
منشور في 2020"…In order to overcome such shortcoming, we develop a generalized algorithm, “ADT” to generate the nonadiabatic equations through symbolic manipulation and to construct highly accurate diabatic surfaces for molecular processes involving excited electronic states. …"
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Algorithm of the brightness scale calibration experiment.
منشور في 2024"…<p>In the algorithm, the following variables were used: “I” denotes the current luminous intensity of the reference diode, “inc” denotes the current difference between reference and target diode luminous intensity; “cnt” is the current number of performed trials, while “correct” is a counter of correct answers in cnt trials, both of them are counted separately for every settings of I and inc. …"
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Data Sheet 1_Establishment of reliable identification algorithms for acute heart failure or acute exacerbation of chronic heart failure using clinical data from a medical informati...
منشور في 2025"…Introduction<p>This study aimed to evaluate the validity of algorithms based on electronic health data in identifying cases of acute heart failure and acute exacerbation of chronic heart failure at multiple institutions using the Medical Information Database Network (MID-NET®) in Japan.…"
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Gillespie algorithm simulation parameters.
منشور في 2024"…Both the ensemble and stochastic models presented in this work have been verified using Monte Carlo molecular dynamic simulations that utilize the Gillespie algorithm. …"
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Scheduling time of five algorithms.
منشور في 2025"…The experimental results show that compared with the traditional particle swarm optimization algorithm, NACFPSO performs well in both convergence speed and scheduling time, with an average convergence speed of 81.17 iterations and an average scheduling time of 200.00 minutes; while the average convergence speed of the particle swarm optimization algorithm is 82.17 iterations and an average scheduling time of 207.49 minutes. …"
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Convergence speed of five algorithms.
منشور في 2025"…The experimental results show that compared with the traditional particle swarm optimization algorithm, NACFPSO performs well in both convergence speed and scheduling time, with an average convergence speed of 81.17 iterations and an average scheduling time of 200.00 minutes; while the average convergence speed of the particle swarm optimization algorithm is 82.17 iterations and an average scheduling time of 207.49 minutes. …"
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Classification and test comparison of padé33-SSVM under different training sample functions.
منشور في 2023الموضوعات: -
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