A Novel Prediction Model for the Sales Cycle of Second-Hand Houses Based on the Hybrid Kernel Extreme Learning Machine Optimized Using the Improved Crested Porcupine Optimizer by Bo Yu, Deng Yan, Han Wu, Junwu Wang, Siyu Chen

“…For this reason, this paper develops a prediction model of the second-hand housing sales cycle based on the hybrid kernel extreme learning machine (HKELM) optimized using the Improved Crested Porcupine Optimizer (CPO), which has achieved rapid and accurate prediction. …”
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Implementation of SVM Algorithm to Predict Song Popularity based on Sentiment Analysis of Lyrics by Quiin Latifah Almatin Lubis, Arif Akbarul Huda

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Robust reinforcement learning algorithm based on pigeon-inspired optimization by Mingying ZHANG, Bing HUA, Yuguang ZHANG, Haidong LI, Mohong ZHENG

“…Reinforcement learning(RL) is an artificial intelligence algorithm with the advantages of clear calculation logic and easy expansion of the model.Through interacting with the environment and maximizing value functions on the premise of obtaining little or no prior information, RL can optimize the performance of strategies and effectively reduce the complexity caused by physical models .The RL algorithm based on strategy gradient has been successfully applied in many fields such as intelligent image recognition, robot control and path planning for automatic driving.However, the highly sampling-dependent characteristics of RL determine that the training process needs a large number of samples to converge, and the accuracy of decision making is easily affected by slight interference that does not match with the simulation environment.Especially when RL is applied to the control field, it is difficult to prove the stability of the algorithm because the convergence of the algorithm cannot be guaranteed.Considering that swarm intelligence algorithm can solve complex problems through group cooperation and has the characteristics of self-organization and strong stability, it is an effective way to be used for improving the stability of RL model.The pigeon-inspired optimization algorithm in swarm intelligence was combined to improve RL based on strategy gradient.A RL algorithm based on pigeon-inspired optimization was proposed to solve the strategy gradient in order to maximize long-term future rewards.Adaptive function of pigeon-inspired optimization algorithm and RL were combined to estimate the advantages and disadvantages of strategies, avoid solving into an infinite loop, and improve the stability of the algorithm.A nonlinear two-wheel inverted pendulum robot control system was selected for simulation verification.The simulation results show that the RL algorithm based on pigeon-inspired optimization can improve the robustness of the system, reduce the computational cost, and reduce the algorithm’s dependence on the sample database.…”
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Lightweight insulator target detection algorithm based on improved YOLOX by Bing Zeng, Wei Hua, Dezhi Li, Zhihao Zhou, Hao Wan, Yunmin Xie, Tangbing Li, Yucong Chen, Jianglei Li, Shenli Wang, Shixun Fu, Zihan Jin, Wenhua Zhang

“…Additionally, Coordinate Attention (CA) is integrated into the detection head to improve the precision of small target detection. Finally, the σWIoU loss function replaces the traditional IoU to accelerate convergence and optimize overall performance. …”
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Improving Integrated Energy Systems With Improved Particle Swarm Optimization: Co-Optimizing Renewables, Electric Vehicles, Gas Systems, and Demand Management by Vahid Khademi, Soodabeh Soleymani, Reza Sharifi, Babak Mozafari

“…The I-PSO algorithm improves optimization performance by about 3.4% compared to competing methods, demonstrating its effectiveness in solving complex energy management problems.…”
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A Multiobjective Brain Storm Optimization Algorithm Based on Decomposition by Cai Dai, Xiujuan Lei

“…Some multiobjective brain storm optimization algorithms have low search efficiency. This paper combines the decomposition technology and multiobjective brain storm optimization algorithm (MBSO/D) to improve the search efficiency. …”
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Optimization of Teaching Management System Based on Association Rules Algorithm by Qing Niu

“…Second, use the MapReduce calculation model to partition the transaction database, then use the improved Apriori optimization algorithm for mining, and finally merge the mining results to obtain frequent itemsets. …”
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Task Offloading Scheme Based on Proximal Policy Optimization Algorithm by Yutong Ma, Junfeng Tian

“…To address this issue, this paper proposes a task offloading scheme based on the Proximal Policy Optimization (PPO) algorithm. On the basis of traditional cloud edge collaborative architecture, the collaborative computing mechanism between edge node devices is further integrated, and the concept of service caching is introduced to reduce duplicate data transmission, reduce communication latency and network load, and improve overall system performance. …”
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Integrated Optimization System for Geotechnical Parameter Inversion Using ABAQUS, Python, and MATLAB by Chengjie Wan, Nianchun Xu, Jiangchao Meng, Junning Chen

“…To improve the optimization process, an adaptive genetic algorithm that dynamically adjusts crossover and mutation rates, thereby improving solution searches and parameter space exploration, is implemented. …”
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Energy Optimal Control Strategy of PHEV Based on PMP Algorithm by Tiezhou Wu, Yi Ding, Yushan Xu

“…Combined with PSO-PI controller and Li-SC HESS internal power limited management approach, the research proposes the PHEV energy optimal control strategy. It is based on revised Pontryagin’s minimum principle (PMP) algorithm, which establishes the PHEV vehicle simulation model through ADVISOR software and verifies the effectiveness and feasibility. …”
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Identification of soil texture and color using machine learning algorithms and satellite imagery by Jiyang Wang

“…For future research, it is recommended to explore the combination of SVR with optimization techniques such as genetic algorithms to further improve the accuracy of soil texture and color predictions.…”
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DEVELOPMENT OF THE ALGORITHM FOR CHOOSING THE OPTIMAL SCENARIO FOR THE DEVELOPMENT OF THE REGION'S ECONOMY by I. S. Borisova

“…It was found that the rationale and choice of the optimal scenario is an important stage in the development of the sustainable development program of the regional economy, since it helps to quantify the most probable trajectories of changes in the activities of all participants in the region's economy.Conclusions and Relevance: the practical significance of the developed algorithm lies in the possibility of using it to improve the stability of the development of the economy of specific regions. …”
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Photovoltaic MPPT Control Method Based on Improved Firefly Algorithm by ZHANG Peng, LUO Zhenghua, TANG Chengda, HUANG Jiangang

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Optimum design of bearingless brushless DC motor modeling with dual loop controller using dragonfly optimizers by Qusay S. Kadhim, Mahmood Swadi, Ali Jafer Mahdi, Mohanad Azeez Joodi, Firas Mohammed Tuaimah, Moanes E. Mohammed, Abbas Hafeth Abbas, Mohamed Salem

“…The proposal's focus consists of two contributions: firstly, the optimal design of the BBLDC motor; secondly, the application of the Dragonfly Algorithm (DA) for the improvement of the motor's control systems, resulting in reduced torque ripple, rapid and precise tracking, and elimination of overshoot. …”
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Modelling of an imprecise sustainable production control problem with interval valued demand via improved centre-radius technique and sparrow search algorithm by Hachen Ali, Md Sadikur Rahman, Ali Akbar Shaikh, Adel Fahad Alrasheedi, Jeonghwan Gwak

“…Abstract The modelling and optimization of a manufacturing systems in the context of sustainable production under uncertainty remain a pivotal focus in control theory. …”
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An optimal weighting-based hybrid classifier for Children's congenital heart diseases signal processing by Morteza Ebrahimpour, Mehdi Khashei

“…The main objective of the proposed optimal weighting-based CNN-LSTM-SVM (OCLS) hybrid classifier is to simultaneously leverage the unique advantages of CNN in feature extraction from input signals, LSTM in modeling the sequential patterns of signals, SVM in classifying regular patterns, and especially the proposed weighting algorithm to optimally integrate the outputs of these components. …”
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Detection of Plants Leaf Diseases using Swarm Optimization Algorithms by Saud Abdul Razzaq, Baydaa Khaleel

“…In this paper, a new method is proposed to classify and distinguish a group of eight different plants to healthy and unhealthy based on the leaf images of these plants They are apples, cherries, grapes, peaches, peppers, potatoes, strawberries, and tomatoes using a hybrid optimization algorithm. In the first stage, the plant leaf images were collected and pre-processed to remove noise and improve contrast. …”
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Prediction and Monitoring Model of Concrete Dam Deformation Based on WOA-RFR by FENG Yu, WU Yunxing, GU Wenjing, PANG Qiong, GU Yanchang, CHEN Siyu

“…The random forest algorithm and whale optimization algorithm were introduced in the construction of the prediction model of concrete dam deformation based on WOA-RFR to improve the prediction accuracy and model performance. …”
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Real Power Loss Reduction by the Cultivation of Soil Optimization Algorithm by Lenin, K.

“…In this paper, the optimal reactive power problem has been solved by the cultivation of soil optimization (CSO) algorithm. …”
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Building Construction Design Based on Particle Swarm Optimization Algorithm by Wenxue Song

“…The relationship between the various risk factors was described by conditional probability, and a safety risk loss-control investment double objective optimization model was built. The corresponding algorithm was designed and the R language programming was used to solve the problem. …”
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