Secure MANET routing with blockchain-enhanced latent encoder coupled GANs and BEPO optimization by Sandeep Jagonda Patil (22048337)

“…The performance of the proposed LEGAN-BEPO-BCMANET technique attains 29.786%, 19.25%, 22.93%, 27.21%, 31.02%, 26.91%, and 25.61% greater throughput, compared to existing methods like Blockchain-based BATMAN protocol utilizing MANET with an ensemble algorithm (BATMAN-MANET), Block chain-based trusted distributed routing scheme with optimized dropout ensemble extreme learning neural network in MANET (DEELNN-MANET), A secured trusted routing utilizing structure of a new directed acyclic graph-blockchain in MANET internet of things environment (DAG-MANET), An Optimized Link State Routing Protocol with Blockchain Framework for Efficient Video-Packet Transmission and Security over MANET (OLSRP-MANET), Auto-metric Graph Neural Network based Blockchain Technology for Protected Dynamic Optimum Routing in MANET (AGNN-MANET) and Data security-based routing in MANETs under key management process (DSR-MANET) respectively.…”

Prediction intervals of probabilities of failure considering that the input variables are linearly scaled Beta(2,2), i.e., the center of mass of the distribution at the center of t... by Luan Carlos de Sena Monteiro Ozelim (16914117)

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Dataset 2: Zip file containing the Tables of the presented method and results by Suchismita Behera (22027316)

Prediction intervals of probabilities of failure considering that the input variables are linearly scaled Beta(5,2), i.e., the center of mass of the distribution closer to the righ... by Luan Carlos de Sena Monteiro Ozelim (16914117)

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Prediction intervals of probabilities of failure considering that the input variables are linearly scaled Beta(2,5), i.e., the center of mass of the distribution closer to the left... by Luan Carlos de Sena Monteiro Ozelim (16914117)

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A* Path-Finding Algorithm to Determine Cell Connections by Max Weng (22327159)

“…The integration of heuristic optimization and machine learning significantly enhances both speed and precision in astrocyte data analysis. …”

Comparison of the WCETs of Lock-MS and DLock-MS, the lower the better. by Alba Pedro-Zapater (8600382)

Prediction intervals of probabilities of failure considering that the input variables are linearly scaled Beta(0.5,0.5), i.e., two centers of mass for the distribution located at b... by Luan Carlos de Sena Monteiro Ozelim (16914117)

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Correlation analysis. by Rongxin Gong (18864603)

“…<i>camphora</i> growth was established using the multiple linear regression (MLR), partial least squares (PLS), support vector regression (SVR), random forest (RF), radial basis function neural network (RBFNN), back propagation neural network (BPNN), and whale optimization algorithm (WOA)-optimized BPNN models. …”

S2 Data - by Rongxin Gong (18864603)

“…<i>camphora</i> growth was established using the multiple linear regression (MLR), partial least squares (PLS), support vector regression (SVR), random forest (RF), radial basis function neural network (RBFNN), back propagation neural network (BPNN), and whale optimization algorithm (WOA)-optimized BPNN models. …”

Research framework diagram. by Rongxin Gong (18864603)

“…<i>camphora</i> growth was established using the multiple linear regression (MLR), partial least squares (PLS), support vector regression (SVR), random forest (RF), radial basis function neural network (RBFNN), back propagation neural network (BPNN), and whale optimization algorithm (WOA)-optimized BPNN models. …”

Model accuracy evaluation. by Rongxin Gong (18864603)

“…<i>camphora</i> growth was established using the multiple linear regression (MLR), partial least squares (PLS), support vector regression (SVR), random forest (RF), radial basis function neural network (RBFNN), back propagation neural network (BPNN), and whale optimization algorithm (WOA)-optimized BPNN models. …”

S3 Data - by Rongxin Gong (18864603)

“…<i>camphora</i> growth was established using the multiple linear regression (MLR), partial least squares (PLS), support vector regression (SVR), random forest (RF), radial basis function neural network (RBFNN), back propagation neural network (BPNN), and whale optimization algorithm (WOA)-optimized BPNN models. …”

S1 File - by Rongxin Gong (18864603)

“…<i>camphora</i> growth was established using the multiple linear regression (MLR), partial least squares (PLS), support vector regression (SVR), random forest (RF), radial basis function neural network (RBFNN), back propagation neural network (BPNN), and whale optimization algorithm (WOA)-optimized BPNN models. …”

Vegetation index calculation formula. by Rongxin Gong (18864603)

“…<i>camphora</i> growth was established using the multiple linear regression (MLR), partial least squares (PLS), support vector regression (SVR), random forest (RF), radial basis function neural network (RBFNN), back propagation neural network (BPNN), and whale optimization algorithm (WOA)-optimized BPNN models. …”

S1 Data - by Rongxin Gong (18864603)

“…<i>camphora</i> growth was established using the multiple linear regression (MLR), partial least squares (PLS), support vector regression (SVR), random forest (RF), radial basis function neural network (RBFNN), back propagation neural network (BPNN), and whale optimization algorithm (WOA)-optimized BPNN models. …”

Model parameters. by Rongxin Gong (18864603)

“…<i>camphora</i> growth was established using the multiple linear regression (MLR), partial least squares (PLS), support vector regression (SVR), random forest (RF), radial basis function neural network (RBFNN), back propagation neural network (BPNN), and whale optimization algorithm (WOA)-optimized BPNN models. …”

Sample statistics. by Rongxin Gong (18864603)

“…<i>camphora</i> growth was established using the multiple linear regression (MLR), partial least squares (PLS), support vector regression (SVR), random forest (RF), radial basis function neural network (RBFNN), back propagation neural network (BPNN), and whale optimization algorithm (WOA)-optimized BPNN models. …”

A Surrogate Machine Learning Model for the Design of Single-Atom Catalyst on Carbon and Porphyrin Supports towards Electrochemistry by Mohsen Tamtaji (10036560)

“…Based on the 2105 DFT calculation data from the literature, we trained a support vector machine (SVR) algorithm. …”

Comparison of mining accuracy. by Shaoxia Mou (16510383)

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