Solving process of gradient-based search. by Tarun Khajuria (12117309)

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GenSearch algorithm. by Tarun Khajuria (12117309)

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S1 File - Solving multi-scenario hybrid flow shop scheduling problem based on an improved probe machine model by Xiang Tian (4369285)

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

EELD problem solving process based on IALO algorithm. by Wenjing Wang (181404)

“…<p>EELD problem solving process based on IALO algorithm.</p>…”

The process of the optimization (MIGA). by Shangyang Jin (21772466)

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Flowchart of the optimization model solving algorithm. by Yihan Liu (2258221)

Optimization process of the DGN method. by Shangyang Jin (21772466)

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The process of the optimization (NSGA-Ⅱ). by Shangyang Jin (21772466)

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The process of the optimization (NSGA-Ⅱ). by Shangyang Jin (21772466)

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Algorithms runtime comparison. by Meilin Zhu (688698)

“…On this basis, considering the changes of customer demands and the speed of distribution network, a partheno-genetic hybrid simulated annealing algorithm is designed to solve the model by using the idea of disruption event processing combining immediate processing and scheduled batch processing. …”

The process of the optimization (NSGA-Ⅱ+ NLPQL). by Shangyang Jin (21772466)

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Parameters of NSGA-II algorithm. by Shangyang Jin (21772466)

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The actual training effect of four algorithms on original photo data (All images are original images taken by the author). by Xiaojun Wang (50332)

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Algorithm pseudocode. by Cheng-jie Chen (22272090)

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An instance of the IPP that can be solved by applying the algorithms for the DPP. by Jordan Moutet (21800145)

Solution results of different algorithms. by Meilin Zhu (688698)

“…On this basis, considering the changes of customer demands and the speed of distribution network, a partheno-genetic hybrid simulated annealing algorithm is designed to solve the model by using the idea of disruption event processing combining immediate processing and scheduled batch processing. …”

The flow chart of the IES program solved by the MSAGOOSE algorithm. by Chengcheng Ding (9013862)

The run time for each algorithm in seconds. by Edward Antonian (21453161)

“…The goal of this paper is to examine several extensions to KGR/GPoG, with the aim of generalising them a wider variety of data scenarios. The first extension we consider is the case of graph signals that have only been partially recorded, meaning a subset of their elements is missing at observation time. …”

Process based on WOA-LSTM-PID model. by Dayu Zhang (710629)

“…The existing temperature control methods, such as the traditional Proportional-Integral-Derivative (PID) controller, are difficult to meet the requirements of OLED for precise temperature control, especially in systems with significant nonlinear and time-varying characteristics. To solve this problem, the study proposes an improved PID controller based on the Long Short-Term Memory (LSTM) optimized by the Whale Optimization Algorithm (WOA). …”