The main components and data flow of the proposed algorithm. by Raed Alharthi (18340157)

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Receiver operator characteristic (ROC) curves of the machine learning algorithms. by Yue Lv (549862)

Algorithmic experimental parameter design. by Chuanxi Xing (20141665)

“…The results of numerical simulations and sea trial experimental data indicate that the use of subarrays comprising 5 and 3 array elements, respectively, is sufficient to effectively estimate 12 source angles. …”

Spatial spectrum estimation for three algorithms. by Chuanxi Xing (20141665)

“…The results of numerical simulations and sea trial experimental data indicate that the use of subarrays comprising 5 and 3 array elements, respectively, is sufficient to effectively estimate 12 source angles. …”

Flowchart of DQN algorithm. by Jiandong Qiu (20389944)

A two-stage robust rescheduling for flexible job shop based on release time prediction using a Q-learning-based hyper-heuristic evolutionary algorithm by Anonymous Authors (for blind review purpose) (20729908)

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Structure and the optimization technique of the algorithms adopted in the study. by M. A. Habib (16839161)

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Data Sheet 1_Enhanced vehicle routing for medical waste management via hybrid deep reinforcement learning and optimization algorithms.pdf by Norhan Khallaf (20710673)

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A two-stage robust rescheduling for flexible job shop based on release time prediction using a Q-learning-based hyper-heuristic evolutionary algorithm by Sihan Yang (18861979)

“…<p dir="ltr">This is the experimental data of the manuscript entitled "A two-stage robust rescheduling for flexible job shop based on release time prediction using a Q-learning-based hyper-heuristic evolutionary algorithm".…”

ML algorithms in cyber security. by Abdullah Asım Yılmaz (20715311)

Feature Importance Analysis of the Algorithms expressed by SHAP indices. by M. A. Habib (16839161)

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Statistical analysis of the prediction results from the ML algorithms. by M. A. Habib (16839161)

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Digital Twin-Driven Reprocessing Scheduling Considering Delayed Differentiation and Urgent Tasks Insertion Using a Hybrid Whale Optimization Algorithm Combined with Q-learning by Authors (for anonymous review purpose) (6946952)

“…<p dir="ltr">This is the experimental data of the manuscript entitled “Digital Twin-Driven Reprocessing Scheduling Considering Delayed Differentiation and Urgent Tasks Insertion Using a Hybrid Whale Optimization Algorithm Combined with Q-learning”.…”

Snapshot of Q-table at some time instance for Q-learning. by Muhammad Waqar (500788)

Top-rated mode of transport based on the SEU algorithm (SEU scores from 0 to 40). by Johannes Weyer (13392175)

Q value model. by Delong Cui (21730915)

Subjects: “…classical heuristic algorithms…”

Performance of various biclustering algorithms on FilmTrust dataset with Q-learning. by Muhammad Waqar (500788)

“…<p>Performance of various biclustering algorithms on FilmTrust dataset with Q-learning.</p>…”

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

“…<div><p>A fault diagnosis method for oil immersed transformers based on principal component analysis and SSA LightGBM is proposed to address the problem of low diagnostic accuracy caused by the complexity of current oil immersed transformer faults. Firstly, data on dissolved gases in oil is collected, and a 17 dimensional fault feature matrix is constructed using the uncoded ratio method. …”

Data Sheet 1_Using reinforcement learning in genome assembly: in-depth analysis of a Q-learning assembler.pdf by Kleber Padovani (10198918)

“…We expand upon the previous approach found in the literature to solve this problem by carefully exploring the learning aspects of the proposed intelligent agent, which uses the Q-learning algorithm. …”

Data_File_1_Q_Learning in IsOWC system.csv by Subhash Suman (20854010)

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