Quadrotor Robust Fractional-Order Control Based on a Recent Bonobo Optimization Algorithm by Faycal Ziani, Aissa Benhammou, Mohamed Amine Hartani, Hegazy Rezk

“…The five fractional parameters for each engine are also improved using the Bonobo Optimization (BO) algorithm. …”
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SGD-TripleQNet: An Integrated Deep Reinforcement Learning Model for Vehicle Lane-Change Decision by Yang Liu, Tianxing Yang, Liwei Tian, Jianbiao Pei

“…This method integrates three types of deep Q-learning networks (DQN, DDQN, and Dueling DDQN) and uses the Stochastic Gradient Descent (SGD) optimization algorithm to dynamically adjust the network weights. …”
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NIRS identification of cashmere and wool fibers based on spare representation and improved AdaBoost algorithm by Zhu Yaolin, Li Zheng, Chen Xin, Chen Jinni, Zhang Hongsong

“…It then uses the sparrow optimization algorithm. It finds the best number and depth of DTs. …”
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Three-Dimensional Path Planning Optimization for Length Reduction of Optimal Path Applied to Robotic Systems by Ilias Chouridis, Gabriel Mansour, Apostolos Tsagaris

“…The 2D path is created by a proposed improved artificial fish swarm algorithm (AFSA) that contains several improvements, such as replacing the random behavior of the fish with a proposed one incorporating the model of the 24 possible movement points and utilizing an introduced model to assist the agent’s navigation called obstacles heatmap. …”
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Smart City Traffic Flow and Signal Optimization Using STGCN-LSTM and PPO Algorithms by Tuxiang Lin, Rongliang Lin

“…Urban traffic congestion remains a critical challenge for smart city development, necessitating innovative approaches to improve traffic flow and reduce delays. This study presents a novel framework that integrates the Spatiotemporal Graph Convolutional Network-Long Short-Term Memory (STGCN-LSTM) model for traffic flow prediction with the Proximal Policy Optimization (PPO) algorithm for dynamic traffic signal control. …”
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Optimization and Scheduling of Integrated Energy Systems with Hydrogen-electricity Coupling Based on PKO Algorithm by Wenli QIN, Na RONG, Xingyan LIU

“…To address the problems of getting stuck in local optima and slow convergence speed during the solution process, the Pied Kingfisher Optimizer (PKO) algorithm was introduced. [Result] The model aims to minimize the total system cost as the objective function, and solves for the optimal scheduling results of the output of each energy network unit; Compared with traditional optimization algorithms, PKO has a faster convergence speed and is better able to achieve the goal of global optimal solution.…”
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Route Optimization of Pipeline in Gas-Liquid Two-Phase Flow Based on Genetic Algorithm by Jun Zhou, Guangchuan Liang, Tao Deng, Jing Gong

“…This paper describes the problems in route optimization of two-phase pipelines. Combining the hydraulic calculation with route optimization theory, this paper establishes an automatic route optimization model and adopts the general genetic algorithm (gGA) and steady-state genetic algorithm (ssGA) to solve the model, respectively, gets the optimal route, and discusses the influence of parameters setting to the result. …”
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UWB Indoor Localization Based on Artificial Rabbit Optimization Algorithm and BP Neural Network by Chaochuan Jia, Can Tao, Ting Yang, Maosheng Fu, Xiancun Zhou, Zhendong Huang

“…The ARO algorithm optimizes the initial weights and thresholds of the BPNN, enabling the model to escape local optima and converge to a global solution. …”
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Predicting the Recurrence of Differentiated Thyroid Cancer Using Whale Optimization-Based XGBoost Algorithm by Keshika Shrestha, H. M. Jabed Omur Rifat, Uzzal Biswas, Jun-Jiat Tiang, Abdullah-Al Nahid

“…Both of our algorithms optimize the hyperparameters of the Extreme Gradient Boosting (XGBoost) model to increase the overall performance. …”
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Arrhythmia detection with transfer learning architecture integrating the developed optimization algorithm and regularization method by Fatma Akalın, Pınar Dervişoğlu Çavdaroğlu, Mehmet Fatih Orhan

“…In this direction, Proposed Optimization Algorithm V5 and Proposed Regularization Method V5 approaches have been integrated into the MobileNetv2 transfer learning model. …”
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Coupling of green building construction based on particle Swarm optimizing neural network algorithm by Wang Leigang, Li Shaohua, Wang Liang, Zhang Zheng, Zhou Yuchen, Chang Long

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HYBRID FIREFLY AND PARTICLE SWARM OPTIMIZATION ALGORITHM FOR DESIGN OF NON-LINEAR CHANNEL EQUALIZER by Vundavalli Ravindra, Pradyumna Kumar Mohapatra, Ravi Narayan Panda, Saroja Kumar Rout

“…This optimum solution has been modelled using the FFA algorithm, which is driven mainly by light intensity attraction. …”
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Credit Rating Model Based on Improved TabNet by Shijie Wang, Xueyong Zhang

“…This manuscript proposes an enhanced credit rating model based on an improved TabNet framework. First, the Kaggle “Give Me Some Credit” dataset undergoes preprocessing, including data balancing and partitioning into training, testing, and validation sets. …”
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Fault diagnosis of ship diesel power distribution system based on WOA-RF algorithm by Weibo LI, Feng GAO, Peng XIAO, Kangzheng HUANG, Daojie RUAN, Junzhuo GAO

“…Therefore, a fault diagnosis method based on whale optimization algorithm-optimized random forest (WOA-RF) is proposed for the marine DG power distribution system.MethodsThe marine DG power distribution system model is built using Matlab/Simulink simulation software. …”
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Prediction of surface deformation time series in closed mines based on LSTM and optimization algorithms by Hu Caixiong, Zhang Lili, Li Haoran, Zhang Yaowen, Yao Yunsheng

“…A long short-term memory (LSTM) neural network combined with the gray wolf optimizer (GWO) algorithm was introduced to improve prediction accuracy. …”
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Optimization of Random Forest Algorithm with Backward Elimination Method in Classification of Academic Stress Levels by Salsabila Dani Amalia, Mula Agung Barata, Pelangi Eka Yuwita

“…Data mining is often used to detect diseases, one of which is the Random Forest algorithm. The Random Forest algorithm is applied as a classification technique for academic stress levels, with optimization using the Backward Elimination method for feature selection to improve model accuracy. …”
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Efficiency management of engineering projects based on particle swarm multi objective optimization algorithm by Xiu Luo, Zhouxin Yi

“…In transportation planning, multi-objective particle swarm optimization algorithm can optimize path planning, improve transportation efficiency and resource utilization.…”
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SMOTE algorithm optimization and application in corporate credit risk prediction with diversification strategy consideration by Han Wei

“…Empirical results demonstrate the optimized SMOTE algorithm’s superiority over six comparison models, such as random over-sampling, under-sampling, etc. …”
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Quality of service optimization algorithm based on deep reinforcement learning in software defined network by Cenhuishan LIAO, Junyan CHEN, Guanping LIANG, Xiaolan XIE, Xiaoye LU

“…Deep reinforcement learning has strong abilities of decision-making and generalization and often applies to the quality of service (QoS) optimization in software defined network (SDN).However, traditional deep reinforcement learning algorithms have problems such as slow convergence and instability.An algorithm of quality of service optimization algorithm of based on deep reinforcement learning (AQSDRL) was proposed to solve the QoS problem of SDN in the data center network (DCN) applications.AQSDRL introduces the softmax deep double deterministic policy gradient (SD3) algorithm for model training, and a SumTree-based prioritized empirical replay mechanism was used to optimize the SD3 algorithm.The samples with more significant temporal-difference error (TD-error) were extracted with higher probability to train the neural network, effectively improving the convergence speed and stability of the algorithm.The experimental results show that the proposed AQSDRL effectively reduces the network transmission delay and improves the load balancing performance of the network than the existing deep reinforcement learning algorithms.…”
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ADVANCE HYDRAULIC SUPPORT MULTI-OBJECTIVE OPTIMIZATION DESIGN BASED ON NSGA-Ⅱ ALGORITHM by NIU YanQi, LIU Wei, ZHANG DeSheng

“…Contrapose the problems of hydraulic support connecting rod mechanical fracture,at the same external load force link mechanical to advance the sum of the absolute values,and minimum quality of the objective function,establishment of a multi-objective optimization model,to solve the optimization used the NSGA-Ⅱ algorithm,using fuzzy set theory method to choose the optimal solution,and has compiled into a visual computing program under matlab environment. …”
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