Solving electric vehicle routing problem with heterogeneous drone and stochastic no-fly zones using enhanced adaptive large neighborhood search algorithm by Anonymous Authors (for blind review purpose) (20729908)

“…<p dir="ltr">This is the experimental data of the manuscript entitled "Solving electric vehicle routing problem with heterogeneous drone and stochastic no-fly zones using enhanced adaptive large neighborhood search algorithm".…”

Solving electric vehicle routing problem with heterogeneous drone and stochastic no-fly zones using enhanced adaptive large neighborhood search algorithm by Wanting Chen (18853951)

“…<p dir="ltr">This is the experimental data of the manuscript entitled "Solving electric vehicle routing problem with heterogeneous drone and stochastic no-fly zones using enhanced adaptive large neighborhood search algorithm".…”

The workflow diagram for the gene expression biomarker study which involve using principal component analysis (PCA) to reduce the number of features (principal components), thus re... by Aninda Astuti (21736334)

Structure determination statistics of HEWL and GI. by Ki Hyun Nam (5813819)

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Molecular replacement (MR) solution and electron density maps of HEWL at various input CTDDs. by Ki Hyun Nam (5813819)

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MR solution and electron density maps of GI at various input CTDDs. by Ki Hyun Nam (5813819)

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Scatter diagram of different principal elements. by Jizhong Wang (7441697)

Code and raw data used in this study. by Zhuolin Yang (14658411)

“…Finally, an edge optimization module is used to integrate the edge features into the middle and the deep supervision layers of the network through an adaptive algorithm to enhance its ability to express edge features and optimize the edge segmentation effect. …”

The performance of the SRMIL and SMRIL algorithms compared to MRMIL, RMIL, and CG_Descent algorithms on the Problems 5.1 to 5.6. by Sulaiman M. Ibrahim (20614376)

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The weight optimization process. by Guomei Cui (20721578)

“…Moreover, the superiority of the model is verified by comparing with the commonly used algorithms such as Support Vector Machine (SVM) and Convolutional Neural Network (CNN). …”

Flowchart of the proposed algorithm. by Md. Rafiqul Islam (403453)

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DataSheet1_Improving the convergence of an iterative algorithm for solving arbitrary linear equation systems using classical or quantum binary optimization.pdf by Erick R. Castro (11243697)

“…<p>Recent advancements in quantum computing and quantum-inspired algorithms have sparked renewed interest in binary optimization. …”

CBR problem-solving process. by Dongling Ma (1269888)

Illustration of how (1 + 1)-WEA_v3 improves the target set when solving TSS. by Alexander Andreev (16822333)

The schematic diagram of fault diagnosis process. by Jialiang Zhang (1574704)

“…In order to improve the training speed and reduces storage, a simplified LSSVM model is used to construct the classifier, and the conjugate gradient algorithm is used for training. …”

Data after data processing. by Jiaqi Wang (369548)

Convergence curves of the investigated algorithms. by Ziad M. Ali (12516532)

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Effects of processing rate and algorithms performance on estimates of biodiversity. by Valentine Fleuré (12822137)

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Comparison of different solution algorithms. by Jinqu Chen (20258031)

Performance profile of the four algorithms based on CPU time. by Sulaiman M. Ibrahim (20614376)

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