Minimax algorithm and machine learning technologies have been studied for decades to reach an ideal optimization in game areas such as chess and backgammon. In these fields, several generations try to optimize the code for pruning and effectiveness of evaluation function. Thus, there are well-armed algorithms to deal with various sophisticated situations in gaming occasion. However, as a traditional zero-sum game, Connect-4 receives less attention compared with the other members of its zero-sum family using traditional minimax algorithm. In recent years, new generation of heuristics is created to address this problem based on research conclusions, expertise and gaming experiences. However, this paper mainly introduced a self-developed heuristics supported by well-demonstrated result from researches and our own experiences which fighting against the available version of Connect-4 system online. While most previous works focused on winning algorithms and knowledge based approaches, we complement these works with analysis of heuristics. We have conducted three experiments on the relationship among functionality, depth of searching and number of features and doing contrastive test with sample online. Different from the sample based on summarized experience and generalized features, our heuristics have a basic concentration on detailed connection between pieces on board. By analysing the winning percentages when our version fights against the online sample with different searching depths, we find that our heuristics with minimax algorithm is perfect on the early stages of the zero-sum game playing. Because some nodes in the game tree have no influence on the final decision of minimax algorithm, we use alpha-beta pruning to decrease the number of meaningless node which greatly increases the minimax efficiency. During the contrastive experiment with the online sample, this paper also verifies basic characters of the minimax algorithm including depths and quantity of features. According to Journal of Intelligent Learning Systems and Applications the experiment, these two characters can both effect the decision for each step and none of them can be absolutely in charge. Besides, we also explore some potential future issues in Connect-4 game optimization such as precise adjustment on heuristic values and inefficiency pruning on the search tree.

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Traditional passive ground wheel drive of peanut planters has displayed poor high-speed seeding performance and the slippage caused in case of sticky and wet soil. Given this, an integrated electric-driven precision seed metering device and controller were designed, which features the application of improved fuzzy PID algorithm. Based on a small peanut planter with one ridge width and duplicate rows, the servo motor drive is used to replace the traditional passive ground wheel. In addition, the satellite speed measurement is employed to complete the electric driving and controlling modification of the seed meter and precise seeding control. A working process mathematical model for the peanut metering device was established to conduct motor speed and field tests which aim at comparing performances between the conventional and the improved fuzzy PID controls. The motor speed trial shows that the average error of the actual speed of the improved fuzzy PID motor was ±1 rad/min, and the coefficient of variation was less than 1%. Against the conventional one, it can better suppress overshoot and improve the response speed. The stable output speed can still be obtained even in case of step changes. Field tests show that when working at medium and low speeds, the qualified rate of plant spacing was greater than 98%, and the rate of missed sowing is <2%; while working at high speed, the qualified rate was greater than 94%, and the rate of missed sowing was less than 4%. The average plant spacing qualification rate of the seed device increased by 6.72%; compared with other electric-driven peanut seed meters, the plant spacing qualification rate increased by 4% during high-speed sowing. In summary, this study has provided an effective technical reference for high-speed precision planting of peanuts.

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In view of the fact that the current ground wheel velocimetry of the peanut precision fertilizer control system cannot solve the phenomenon of ground wheel slippage, and signal interference and delay loss cannot be excluded by BeiDou positioning velocimetry, a set of peanut precision fertilizer control system was designed based on the threshold speed algorithm. The system used STM32F103ZET6 microcontroller as the main controller, and touch screen for setting the operating parameters such as operating width, fertilizer type, and fertilizer application amount. The threshold speed algorithm combined with BeiDou and ground wheel velocimetry was adopted to obtain the forward speed of the tractor and adjust the speed of the DC drive motor of the fertilizer applicator in real time to achieve precise fertilizer application. First, through the threshold speed algorithm test, the optimal value of the length N of the ground wheel speed measurement queue was determined as 3, and the threshold of the speed variation coefficient was set to 4.6%. Then, the response performance of the threshold speed algorithm was verified by comparative test with different fertilization amounts (40 kg/hm 2 , 50 kg/hm 2 , 60 kg/hm 2 , 70 kg/hm 2 ) under two speed acquisition methods of ground wheel speed measurement and threshold speed algorithm (combination of Beidou single-point speed and ground wheel speed measurement) in different operation speeds (3 km/h, 4 km/h, 5 km/h). The response performance test results showed that the average value of the velocimetry delay distance of the BeiDou single-point positioning velocimetry method was 0.58 m, while the average value of that with the threshold velocity algorithm was 0.27 m, which decreased by 0.31 m and indicated more accurate with the threshold velocity algorithm. The field comparison test for fertilizer application performance turned out an over 96.08% accuracy rate of fertilizer discharge by applied with the threshold speed algorithm, which effectively avoided the inaccurate fertilizer application caused by wheel slippage and raised the accuracy of fertilizer discharge by at least 1.2% compared with that of using the ground wheel velocimetry alone. The results showed that the threshold speed algorithm can meet the requirements of precise fertilizer application.