The classification model of ELM,\(g(x) = h(x)\delta\), where \(h(x)\) is the mapping function matrix, \(\delta = \left[ {\delta_{1} , \ldots ,\delta_{L} } \right]^{T}\) is the weight vector connecting the output layer and the hidden layer,
Category: 7. Maths
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A novel fault diagnosis method for gearbox based on RVMD and TELM with composite chaotic grey wolf optimizer
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Cognitive bias in clinical large language models
Biases affecting clinical LLM systems can arise at multiple stages, including data-related biases from collection and representation, model-related biases from algorithm design and training, and deployment-related biases stemming from real-world…
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Aqua-MC as a simple open access code for uncountable runs of AquaCrop
Ma, H. et al. Time series global sensitivity analysis of genetic parameters of CERES-maize model under water stresses at different growth stages. Agric. Water Manag. 275, 108027. https://doi.org/10.1016/j.agwat.2022.108027 (Jan. 2023).
Ramezani…
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Local and global sensitivity analysis for a prediction model of nitrogen loss in Southern China’s paddy fields via HYDRUS-1D
Local sensitivity analysis
LSA is employed to analyze the importance of the seven uncertain parameters (μ′w,1, μ′s,2, μ′w,2, μw,3, dmix, p and α) for the predicted nitrogen concentrations in surface runoff and soil in paddy fields….
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A novel meta-heuristic algorithm based on candidate cooperation and competition
Inspiration
High schools are vital institutions shaping societal elites and professionals, significantly contributing to a nation’s development through high-quality education. The entrance examination system varies globally, with Western…
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Project based learning framework integrating industry collaboration to enhance student future readiness in higher education
The study aims to assess the impact of integrating direct industry perspectives within an expanded PBL curriculum on cultivating future readiness competencies among undergraduate university students by quantitative analysis. As industries…
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A Multi-Scale attention network for building extraction from high-resolution remote sensing images
The experiments were designed and implemented using the Keras deep learning framework. Programming was conducted using the PyCharm and Anaconda software. The experimental setup comprised the following: a Linux operating system, equipped with 2…
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Leveraging explainable artificial intelligence for early detection and mitigation of cyber threat in large-scale network environments
This work introduces a novel LXAIDM-CTLSN method. The aim is to detect and classify cyberattacks to achieve cybersecurity. The LXAIDM-CTLSN model encompasses processes such as data normalization, MOA-based feature selection, SDAE-based…
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A CAE model-based secure deduplication method
In traditional autoencoder models, assuming the number of labels in the label library is \(|T| = n\), the algorithm’s time complexity is \(O(n)\). The performance bottleneck lies in the compareTag method, which requires bilinear mapping…
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Dynamic appliance scheduling and energy management in smart homes using adaptive reinforcement learning techniques
The suggested model seeks to improve smart home energy management through optimized energy use, cost minimization, and enhanced user satisfaction. It uses real-time energy prices to schedule appliances for optimization, taking into account user…
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