بدائل البحث:
model optimization » codon optimization (توسيع البحث), global optimization (توسيع البحث), based optimization (توسيع البحث)
primary data » primary care (توسيع البحث)
data process » data processing (توسيع البحث), damage process (توسيع البحث), data access (توسيع البحث)
binary path » binary data (توسيع البحث), binary health (توسيع البحث), binary pairs (توسيع البحث)
path model » each model (توسيع البحث)
model optimization » codon optimization (توسيع البحث), global optimization (توسيع البحث), based optimization (توسيع البحث)
primary data » primary care (توسيع البحث)
data process » data processing (توسيع البحث), damage process (توسيع البحث), data access (توسيع البحث)
binary path » binary data (توسيع البحث), binary health (توسيع البحث), binary pairs (توسيع البحث)
path model » each model (توسيع البحث)
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Proposed reinforcement learning architecture.
منشور في 2025"…<div><p>In the realm of game playing, deep reinforcement learning predominantly relies on visual input to map states to actions. The visual data extracted from the game environment serves as the primary foundation for state representation in reinforcement learning agents. …"
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84
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Inconsistency concept for a triad (2, 5, 3).
منشور في 2025"…The proposed regeneration method emulates three primary phases of a biological process: identifying the most damaged areas (by identifying inconsistencies in the pairwise comparison matrix), cell proliferation (filling in missing data), and stabilization (optimization of global consistency). …"
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86
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Trace, Machine Learning of Signal Images for Trace-Sensitive Mass Spectrometry: A Case Study from Single-Cell Metabolomics
منشور في 2019"…However, extraction of trace-abundance signals from complex data sets (<i>m</i>/<i>z</i> value, separation time, signal abundance) that result from ultrasensitive studies requires improved data processing algorithms. …"
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89
Trace, Machine Learning of Signal Images for Trace-Sensitive Mass Spectrometry: A Case Study from Single-Cell Metabolomics
منشور في 2019"…However, extraction of trace-abundance signals from complex data sets (<i>m</i>/<i>z</i> value, separation time, signal abundance) that result from ultrasensitive studies requires improved data processing algorithms. …"
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90
MCLP_quantum_annealer_V0.5
منشور في 2025"…<p dir="ltr">Geospatial optimization problems are fundamental research issues in geographic information science modeling, characterized by high dimensionality, dynamics, and discreteness. …"
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91
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94
Supporting data for “The role of forest composition heterogeneity on temperate ecosystem carbon dynamic under climate change"
منشور في 2025"…The process includes (1) harmonizing Landsat 5, 7, 8, and Sentinel-2 data using the HLS algorithm, and (2) filling temporal gaps with an optimized object-based STARFM fusion algorithm. …"
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95
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Data used to drive the Double Layer Carbon Model in the Qinling Mountains.
منشور في 2024"…It also incorporates climate change responses, adjust decomposition rates based on climate and environmental changes, and lead to robust estimates under different climatic scenarios. The simulation process of the DLCM involves initializing SOC stocks with spatially detailed baseline data, adding organic matter inputs based on vegetation production, and simulating microbial decomposition while adjusting for climate variables such as temperature and soil moisture. …"
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98
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SPAM-XAI confusion matrix.
منشور في 2024"…We propose SPAM-XAI, a hybrid model integrating novel sampling, feature selection, and eXplainable-AI (XAI) algorithms to address these challenges. The SPAM-XAI model reduces features, optimizes the model, and reduces time and space complexity, enhancing its robustness. …"