Yuan Biao Zhang’s research while affiliated with University of Jinan and other places

Two aspects in "sweet spot" choosing are defined: the furthest batted-ball displacement and the highest fine-territory probability. A model to determine the "sweet spot" position on the bat is developed based on physical mechanics and probability theory. Combing contributions of velocity resolution and Fuzzy distribution, a global fair-territory probability is synthetically determined. Simulation result of the "sweet spot" shows that the "sweet spot" goes around 14 cm from the end of the bat.

The paper is aimed at forecasting the locations of next crime. Based on local demographic factors, geographic factors and environment psychological factors, it establishes a Multi-factor Evaluation Model. We then use an actual case (The Yorkshire Ripper case) for model testing, and get good test results.

. In this paper, we provide a Sweet Spot Model for two problems: where the “Sweet Spot” is and how the bat affects the hitting-effect. Our model is very close to live. And we can find the exact position of Sweet Spot and see the relationship between the rebound velocity of the ball after hitting and the factors of hitting point, such as the speed of bat before hitting, the speed of the ball before hitting, Coefficient of Restitution (COR) (a constant determined by the bat material), the mass distribution of bat and so on. After that, we apply our model to corked bats and study the influence of “corking”.

To strengthen monitoring for plastic debris in the ocean, our paper compared debris distributions of 2 special Garbage Patches (The North Pacific Central Gyre and Kuroshio Current area). And then we developed a computer-based optimal searching model to monitor formation and changes of debris in the oceans. We found that winds belts, currents, and regional human activities along with seasonal climatic variations can influence marine litter patterns and trends in deposition.

This paper analyzes the formation of the Great Pacific Ocean Garbage Patch and its negative influences. Then, for evaluating the effectiveness and feasibility of these methods, we conduct cost-effect analysis on the economic costs and benefits; and undertake an analysis on the effects of the solutions concerning social benefits; then, establish a comprehensive evaluation model of solutions after combining the economic and social factors, which eventually gives birth to workable policy recommendations.

To reduce the cost of food inspection, we built a minimum cost sampling inspection model on the basis of simple random sampling, and ensured that the reliability of sampling inspection lived up to the required reliability at the same time. In this model, according to the relationship between inspected qualified rate and standard qualified rate, we adjusted the sample size through relaxing and tightening the inspection. The result shows that this plan can greatly reduce the inspect cost. Besides, the model is flexible, and it can formulate different sampling inspection plans according to the required reliability.

This paper presents a solution of the Optimal Tolerance Design Problems for the production of power transformers. Based on statistical and probabilistic methods, it establishes a multi-objective and multi-constraint mathematical model. We then present a solution that maximizes the effective utilization rate of sheet material, for producing core columns of power transformers, and the passing rate of quality controls of matching coils and cores. It also minimizes the Tolerance cost of the product. The solution uses Particle Swarm Optimization (PSO), which is very effective as shown by simulation results.

In terms of the design of the Core Section, aiming at the half of the core circumcircle, for the case of the Core Section without the Cooling Oil Pan, this paper firstly establishes a non-linear programming model taking the objective function that the geometric cross-sectional area of the column core is the largest. Then, on the basis of analyzing the case of Cross Section with the Cooling Oil Pans another non-linear programming model is estabished to make the geometric cross-sectional area of the core column be the largest and the adjacent area of the two parts divided by the Cooling Oil Pans be equal as much as possible. And, the series of the section and the width and thickness of the silicon steel sheets at all levels are fixed while the effective cross-section of the core column is maximum. At last, to the two instances, this paper analyses the effects of the addition of the Cooling Oil Pans on the design for Cross Section.

Based on the related current researches, this disquisition is focused on the problem of plastic debris in the Great Pacific Ocean Garbage Patch. From three aspects-the extent, density and distribution, this disquisition made a research on the current situation of the serious problem, and then put forward a quantitative model of the weight of plastic debris in the Pacifi Ocean Gyre. Besides, by limiting polystyrene takeout containers, we established an iterative model to predict the weight of plastic debris access to the sea per year in the future. After proving limiting polystyrene takeout containers could reduce the plastic debris effectively, we carry on a detailed analysis.

Order arrangement is always the headache thing for manufacturers even in this high-tech modern society. Hence, this paper manages to construct a nonlinear 0-1 programming mathematical model in search of optimal solution of minimizing the cost of default. And we make an attempt to apply Genetic Algorithm in accordance with this NP-hard problem. In designing the algorithm, we propose an encoding method based both on orders and working procedure, adopt Roulette Wheel method to select the next generation, and embed crossover and mutation to avoid the common defect of premature convergence. Noticing that firms would have various psychological preferences towards different orders, we introduce Membership Function to characterize the priority of orders by comprehensively concern processing complexity, urgency and revenue of orders.