Predicting county level corn yields using deep, long, short-term memory models in the Corn Belt

Having an accurate corn yield prediction is useful because it provides information about production and equilibrium post-harvest futures price prior to harvest. A publicly available corn yield prediction can help address emergent information asymmetry problems and, in doing so, improve price efficiency on futures markets. This paper is the first to predict corn yield using Long Short-Term Memory (LSTM), a special Recurrent Neural Network method. Our prediction is only 0.83 bushel/acre lower than actual corn yields in the Corn Belt, and is more accurate than the pre-harvest prediction from the USDA. And more importantly, our model provides a publicly available source that will contribute to eliminating the information asymmetry problem that arises from private sector crop yield prediction

Adaptive and Robust Fault-Tolerant Tracking Control of Contact force of Pantograph-Catenary for High-Speed Trains

Abstract This paper presents a modified multi-body dynamic model and a linear time-invariant model with actuator faults (loss of effectiveness faults, bias faults) and matched and unmatched uncertainties. Based on the fault model, a class of adaptive and robust tracking controllers are proposed which are adjusted online to tolerate the time-varying loss of effectiveness faults and bias faults, and compensate matched disturbances without the knowledge of bounds. For unmatched uncertainties, optimal control theory is added to the controller design processes. Simulations on a pantograph are shown to verify the efficiency of the proposed fault-tolerant design approach

Optimal design of blade parameters for fracturing tea-picking machine

The blade is one of the most critical components in the fracturing tea-picking machine, and this study is conducted to optimize the blade's working parameters. In this study, the effects of blade width, blade thickness, and cutting angle on the maximum fracturing force of tea stems were analyzed using the L9 (34) standard orthogonal table, with the maximum fracturing force used as the evaluation index. The results indicate that the main factors affecting the maximum fracturing force (MFF) of tea stems are cutting angle (CA), blade width (BW), and blade thickness (BT) in that order. Furthermore, microscopic observation of the fracture surface revealed that compared with the thickness of the other two blades, the thickness of 0 mm caused the cross-section uneven and had lots of burrs, correspondingly resulting in the section's oxidation and the deterioration of tea leaf quality. Therefore, the optimal combination of design parameters was a cutting angle of 90°, a blade width of 2.0 mm, and a blade thickness of 0.5 mm. The findings of this study can provide reference for blade design to reduce the fracturing force of tea-picking machines, lower the working power consumption, and improve the quality of freshly plucked tea leaves

Adaptive Actuator Compensation of Position Tracking for High-Speed Trains with Disturbances

In this paper, the adaptive fault compensation prob-lem is investigated for high-speed trains in the presence of time-varying system parameters, disturbances and actuator failures. To deal with the time-varying system parameters, a new time-varying indicator function instead of commonly used 0-1 function, is proposed to model the train dynamics as a piecewise model with unparameterizable time-varying disturbances, which can cover more time variations and help parametrization for adaptation. A backstepping adaptive controller is designed for the healthy system with unknown piecewise model parameters and known piecewise bounds on disturbances. For both the parameterizable and unparameterizable failures, the backstepping adaptive fail-ure compensation with the adaptive laws are derived to achieve the position tracking under the known bound disturbances. The adaptive failure compensation for unknown bounds on disturbances is also discussed under the parameterizable failure. Through introducing the nonlinear damping in the proposed controller, the failure compensation controller is proposed for the model with unparameterizable system parameters to achieve an arbitrary degree of position tracking accuracy. The stability of the corresponding closed-loop system and asymptotic state tracking are proved via Lyapunov direct method, and validated using a high-speed train model

Adaptive Control Design and Evaluation for Multibody High-speed Train Dynamic Models

In this paper, the adaptive tracking control problem is investigated for multibody high-speed train dynamic model in the presence of unknown parameters, which is an open adaptive control problem. A 4-car train unit model with input signals acting on the 2nd and 3rd cars and output signals being the speeds of the 1st and 3rd cars is chosen as a benchmark model, in which the aerodynamic resistance force is also considered. To handel the nonlinear term, the feedback linearization method is employed to decompose the system into a control dynamics subsystem and a zero dynamics subsystem. A new and detailed stability analysis is conducted to show that such a zero dynamic system is Lyapunov stable and is also partially input-to-state stable under the condition that the speed error between the 1st and 3rd cars is exponentially convergent (to be ensured by a nominal controller) or belongs to the L1 signal space (to be achieved by a properly designed adaptive controller). The system configuration leads to a relative degree 1 subsystem and a relative degree 2 subsystem, for which different feedback linearization-based adaptive controllers and their nominal versions are developed to ensure the needed stabilization condition, the desired closed-loop system signal boundedness and asymptotic output speed tracking. Detailed closed-loop system stability and tracking performance analysis are given for the new control schemes. Simulation results from a realistic train dynamic model are presented to verify the desired adaptive control system performance

Improving Photostability and Antifungal Performance of Bamboo with Nanostructured Zinc Oxide

We report on the formation of zinc oxide (ZnO) films with various morphologies on bamboo to simultaneously furnish it with excellent photostability and antifungal properties. A simple two-step process was adopted, consisting of generation of ZnO seeds on the bamboo surface followed by solution treatment to promote crystal growth. Effect of reaction conditions on film morphologies was systematically investigated. Results indicate morphologies of ZnO films can be tailored from nanoparticles to nanostructured networks and irregular aggregates at the micron scale with different crystallinities through specific combinations of reaction conditions. The photostability and antifungal performances of coated bamboo were greatly improved and highly dependent on both crystallinity and morphologies of ZnO films

Mixed leaf litter decomposition and N, P release with a focus on Phyllostachys edulis (Carrière) J. Houz. forest in subtropical southeastern China

As an important non-wood forest product and wood substitute, Moso bamboo grows extremely rapidly and hence acquires large quantities of nutrients from the soil. With regard to litter decomposition, N and P release in Moso bamboo forests is undoubtedly important; however, to date, no comprehensive analysis has been conducted. Here, we chose two dominant species (i.e., Cunninghamia lanceolata and Phoebe bournei), in addition to Moso bamboo, which are widely distributed in subtropical southeastern China, and created five leaf litter mixtures (PE100, PE80PB20, PE80CL20, PE50PB50 and PE50CL50) to investigate species effects on leaf litter decomposition and nutrient release (N and P) via the litterbag method. Over a one-year incubation experiment, mass loss varied significantly with litter type (P 0.94, P < 0.001). N and P had different patterns of release; overall, N showed great temporal variation, while P was released from the litter continually. The mixture of Moso bamboo and Phoebe bournei (PE80PB20 and PE50PB50) showed significantly faster P release compared to the other three types, but there was no significant difference in N release. Litter decomposition and P release were related to initial litter C/N ratio, C/P ratio, and/or C content, while no significant relationship between N release and initial stoichiometric ratios was found. The Moso bamboo–Phoebe bournei (i.e., bamboo–broadleaved) mixture appeared to be the best choice for nutrient return and thus productivity and maintenance of Moso bamboo in this region

Development of Creep Models for Glued Laminated Bamboo Using the Time-Temperature Superposition Principle

This paper describes the development of creep models for glued laminated bamboo (GLB)using the time-temperature superposition principle (TTSP). Creep (15 min) and recovery (45 min) data were obtained at constant temperature levels ranging from 25 to 65C. The moisture contents of specimens for testing were dry, 7% and 12%. The individual curve at each temperature was plotted against the log-time axis to obtain a master curve. A nonlinear regression analysis was used to estimate the model parameters. Then the individual temperature master curves were shifted again to a reference MC to construct an overall master curve using time-temperature-moisture principle. The relation of temperature and moisture shift factors loga (T, M) to temperature (T) and MC (M) was analyzed. The results show that the TTSP was successfully applied to GLB tested at different moisture contents