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density function » density functional (Expand Search)
algorithm pca » algorithm fa (Expand Search), algorithm goa (Expand Search), algorithm a (Expand Search)
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Accommodating High Penetrations of Renewable Distributed Generation Mix in Smart Grids
Published 2017Subjects: Get full text
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Distributed optimal coverage control in multi-agent systems: Known and unknown environments
Published 2024Subjects: -
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BUC algorithm for iceberg cubes
Published 2003“…In this paper, we implement the Bottom-Up Computation (BUC) algorithm for computing Iceberg cubes and conduct a sensitivity analysis of BUC with respect to the probability density function of the data. …”
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Label dependency modeling in Multi-Label Naïve Bayes through input space expansion
Published 2024“…To accommodate the heterogeneity of the expanded input space, we refine the likelihood parameters of iMLNB using a joint density function, which is adept at handling the amalgamation of data types. …”
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Optimization of Commercially Off the Shelf (COTS) Electric Propulsion System for Low Speed Fuel Cell UAV
Published 2013Get full text
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Energy-Efficient Computation Offloading in Vehicular Edge Cloud Computing
Published 2020“…Subsequently, we propose a method to measure the cost-effectiveness of allocated resources and energy savings, named value density function. Interestingly, with respect to the amount of allocation resource, it can obtain the maximum value density when offloading energy consumption equals to half of local energy consumption. …”
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IMPROVING BER PERFORMANCE OF LDPC CODES BASED ON INTERMEDIATE DECODING RESULTS
Published 2007“…The paper presents a novel approach to reduce the bit error rate (BER) in iterative belief propagation (BP) decoding of low density parity check (LDPC) codes. The behavior of the BP algorithm is first investigated as a function of number of decoder iterations, and it is shown that typical uncorrected error patterns can be classified into 3 categories: oscillating, nearly-constant, or random-like, with a predominance of oscillating patterns at high Signal-to-Noise (SNR) values. …”
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Diagnostic structure of visual robotic inundated systems with fuzzy clustering membership correlation
Published 2023“…Additionally, a clustering algorithm with a fuzzy membership function is implemented, allowing the robots to advance in accordance with predefined clusters and arrive at their starting place within a predetermined amount of time. …”
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Improving the Resilience of Smart Distribution Networks against Cyber Attacks
Published 2022Get full text
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StackDPPred: Multiclass prediction of defensin peptides using stacked ensemble learning with optimized features
Published 2024“…Next, principal component analysis (PCA) is used to select the best subset of attributes. …”
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Exploring the Dynamic Interplay of Deleterious Variants on the RAF1–RAP1A Binding in Cancer: Conformational Analysis, Binding Free Energy, and Essential Dynamics
Published 2024“…Principal component analysis (PCA) and free energy landscape (FEL) evaluation further determined dynamical variations in the wild‐type and mutant complexes. …”
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Traffic Offloading with Channel Allocation in Cache-Enabled Ultra-Dense Wireless Networks
Published 2018“…We generate results as a function of a wide range of system parameters, and demonstrate that the proposed algorithms achieve near-optimal performance with notably low time complexity.…”
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Intelligent route to design efficient CO<sub>2</sub> reduction electrocatalysts using ANFIS optimized by GA and PSO
Published 2022“…In doing so, to represent the surface properties of the electrocatalysts numerically, d-band theory-based electronic features and intrinsic properties obtained from density functional theory (DFT) calculations were used as descriptors. …”
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DeepRaman: Implementing surface-enhanced Raman scattering together with cutting-edge machine learning for the differentiation and classification of bacterial endotoxins
Published 2025“…Unlike standard machine learning approaches such as PCA, LDA, SVM, RF, GBM etc, DeepRaman functions independently, requiring no human interaction, and can be used to much smaller datasets than traditional CNNs. …”
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