A Pork Price Prediction Model Based on a Combined Sparrow Search Algorithm and Classification and Regression Trees Model

Qin, Jing; Yang, Degang; Zhang, Wenlong

doi:10.3390/app132312697

Cited by 3 publications

(1 citation statement)

References 69 publications

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“…Therefore, improving the SSA algorithm has become a research hotspot. Qin et al [27] combined the sparrow search algorithm with the traditional machine learning model Classification and Regression Trees (CART) to establish an SSA-CART optimization model for predicting pork prices. Jianhua and Zhiheng [28] proposed an optimization strategy that integrates the butterfly optimization algorithm (BOA).…”

Section: Introductionmentioning

confidence: 99%

Application of a Multi-Strategy Improved Sparrow Search Algorithm in Bridge Crane PID Control Systems

Zhang,

Liu,

Liang

et al. 2024

Applied Sciences

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To address the anti-swing issue of the payload in bridge cranes, Proportional–Integral–Derivative (PID) control is a commonly used method. However, parameter tuning of the PID controller relies on empirical knowledge and often leads to system overshoot. This paper proposes an Improved Sparrow Search Algorithm (ISSA) to optimize the gains of PID controllers, alleviating adverse effects on payload oscillation and trolley positioning during the operation of overhead cranes. First, tent map chaos mapping is introduced to initialize the sparrow population, enhancing the algorithm’s global search capability. Then, by integrating sine and cosine concepts along with nonlinear learning factors, the updating mechanism of discoverer positions is dynamically adjusted, expediting the solving process. Finally, the Lévy flight strategy is employed to update follower positions, thereby enhancing the algorithm’s local escape capability. Additionally, a fitness function containing overshoot penalties is proposed to address overshoot issues. Simulation results indicate that the overshoot rates of all algorithms remain less than 3%. Moreover, compared with the Sparrow Search Algorithm (SSA), Particle Swarm Optimization (PSO), Simulated Annealing (SA), and Whale optimization Algorithm (WOA), the optimized PID control system with the ISSA algorithm exhibits superior control performance and possesses certain robustness and adaptability.

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Section: Introductionmentioning

confidence: 99%

Application of a Multi-Strategy Improved Sparrow Search Algorithm in Bridge Crane PID Control Systems

Zhang,

Liu,

Liang

et al. 2024

Applied Sciences

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Exploration of College Students’ Psychological Education Teaching Mode Based on Cognitive Behavioral Theory and Its Practice in the Internet Era

Xiang,

Zhao

2024

Applied Mathematics and Nonlinear Sciences

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The Internet era brings to the teaching of mental health courses not only the sharing of the best quality teaching resources, but also will profoundly impact the traditional teaching mode of mental health education classes. Based on Cognitive Behavioral Theory (CBT), this study constructed a hybrid online + offline psychological education teaching mode in the Internet era and designed a controlled experiment between it and the traditional teaching mode to analyze the significant difference through the independent samples t-test method to realize the comparative analysis of the teaching mode. Additionally, the influence factors for evaluating the effectiveness of the teaching method were explored using the CART categorical regression tree model. In Group I, which adopted the blended teaching mode, there were significant differences in the male students’ mental health factors in obsessive-compulsive (p=0.013) and paranoia (p=0.014) and highly significant differences in interpersonal relationships (p=0.006) and academic stress (p=0.002). There is a significant difference in the mental health factors of female students in five factors: compulsion, interpersonal relationship, anxiety, maladjustment, and emotional instability, and there is a highly significant difference in paranoia and academic stress. Only the compulsive (male) factor (p=0.029) and depression (female) factor (p=0.031) showed significant differences in each health factor before and after the experiment in Group II, which used the traditional teaching mode. The teaching mode of this paper has an obvious effect on the improvement of college students’ mental health, which is much better than the traditional teaching mode, thus providing feasible ideas for the construction of a psychological education teaching mode.

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Monthly Pork Price Prediction Applying Projection Pursuit Regression: Modeling, Empirical Research, Comparison, and Sustainability Implications

Yu,

Liu,

Lai

2024

Sustainability

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The drastic fluctuations in pork prices directly affect the sustainable development of pig farming, agriculture, and feed processing industries, reducing people’s happiness and sense of gain. Although there have been extensive studies on pork price prediction and early warning in the literature, some problems still need further study. Based on the monthly time series data of pork prices and other 11 influencing prices (variables) such as beef, hog, piglet, etc., in China from January 2000 to November 2023, we have established a project pursuit auto-regression (PPAR) and a hybrid PPAR (H-PPAR) model. The results of the PPAR model study show that the monthly pork prices in the lagged periods one to three have an important impact on the current monthly pork price. The first lagged period has the largest and most positive impact. The second lagged period has the second and a negative impact. We built the H-PPAR model using the 11 independent variables (prices), including the prices of corn, hog, mutton, hen’s egg, and beef in lagged period one, the piglet’s price in lagged period six, and by deleting non-important variables. The results of the H-PPAR model show that the hog price in lagged period one is the most critical factor, and beef price and the other six influencing variables are essential factors. The model’s performance metrics show that the PPAR and H-PPAR models outperform approaches such as support vector regression, error backpropagation neural network, dynamic model average, etc., and possess better suitability, applicability, and reliability. Our results forecast the changing trend of the monthly pork price and provide policy insights for administrators and pig farmers to control and adjust the monthly pork price and further enhance the health and sustainable development of the hog farming industry.

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A Pork Price Prediction Model Based on a Combined Sparrow Search Algorithm and Classification and Regression Trees Model

Cited by 3 publications

References 69 publications

Application of a Multi-Strategy Improved Sparrow Search Algorithm in Bridge Crane PID Control Systems

Application of a Multi-Strategy Improved Sparrow Search Algorithm in Bridge Crane PID Control Systems

Exploration of College Students’ Psychological Education Teaching Mode Based on Cognitive Behavioral Theory and Its Practice in the Internet Era

Monthly Pork Price Prediction Applying Projection Pursuit Regression: Modeling, Empirical Research, Comparison, and Sustainability Implications

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