硝酸钠卤水沸点变化理论计算

根椐已有的文献与数据,采用数学模型方法,研究了硝酸钠卤水沸点在不同组成、不同压力条件下的变化关系,确定了硝酸钠卤水沸点与质量分数及压力的数学方程式;根椐硝酸钠卤水压力与组成,可以计算出硝酸钠卤水的沸点值,为新疆都善县库木塔格硝酸钠矿大规模生产硝酸钠提供了重要设计依据.     

伪随机流场法在堤坝渗漏探测中的应用与研究

伪随机流场法具有快捷、直接、精确有效等优点,逐步成为堤坝渗漏探测的主流方法。利用该方法,在漏水区域、库区无穷远段进行高压供电,库区内网格状布置测点,可查找渗漏入水点。通过对各异常区域的区域面积、异常区域内各测点的异常平均值以及对于严重渗漏的临界值进行计算,可判断水库渗漏通道和各渗漏点的渗漏量比例。此外,由于该方法快速便捷的特点,可以运用该方法进行实时监测。应用于某混凝土面板堆石坝的探测结果表明,利用堤坝周边已经存在的监测孔或在灌浆帷幕下游进行钻孔,进行伪随机电位差或者电流测试,可在无损条件下判断渗漏来源和通道发育方向,检测防渗处理效果。该方法可为堤坝渗漏监测预警、拟定防渗处理方案提供依据。     

Time series forecasting by neural networks: A knee point-based multiobjective evolutionary algorithm approach

In this paper, we investigate the problem of time series forecasting using single hidden layer feedforward neural networks (SLFNs), which is optimized via multiobjective evolutionary algorithms. By utilizing the adaptive differential evolution (JADE) and the knee point strategy, a nondominated sorting adaptive differential evolution (NSJADE) and its improved version knee point-based NSJADE (KP-NSJADE) are developed for optimizing SLFNs. JADE aiming at refining the search area is introduced in nondominated sorting genetic algorithm II (NSGA-II). The presented NSJADE shows superiority on multimodal problems when compared with NSGA-II. Then NSJADE is applied to train SLFNs for time series forecasting. It is revealed that individuals with better forecasting performance in the whole population gather around the knee point. Therefore, KP-NSJADE is proposed to explore the neighborhood of the knee point in the objective space. And the simulation results of eight popular time series databases illustrate the effectiveness of our proposed algorithm in comparison with several popular algorithms.     

Fuzzy度量空间上映射的又一个不动点定理

继文献〔1〕之后证明了Fuzzy度量空间上映射的又一个不动点定理，使文献〔2〕的§1（3，4）的定理成为本文的特例。     

多点多板多分型面注塑模具的简化设计

应用锁扣装置、组合拉杆结构，减少导柱数量，简化了多点多板多分型面注塑模具的设计。     

Reliability-based robust design optimization: A general methodology using genetic algorithm

In this paper, we present an improved general methodology including four stages to design robust and reliable products under uncertainties. First, as the formulation stage, we consider reliability and robustness simultaneously to propose the new formulation of reliability-based robust design optimization (RBRDO) problems. In order to generate reliable and robust Pareto-optimal solutions, the combination of genetic algorithm with reliability assessment loop based on the performance measure approach is applied as the second stage. Next, we develop two criteria to select a solution from obtained Pareto-optimal set to achieve the best possible implementation. Finally, the result verification is performed with Monte Carlo Simulations and also the quality improvement during manufacturing process is considered by identifying and controlling the critical variables. The effectiveness and applicability of this new proposed methodology is demonstrated through a case study.     

Effects of prior knowledge on learning from different compositions of representations in a mobile learning environment

Two experiments examined the effects of prior knowledge on learning from different compositions of multiple representations in a mobile learning environment on plant leaf morphology for primary school students. Experiment 1 compared the learning effects of a mobile learning environment presenting text and photos of plants on a tablet PC, either in combination with or without real plants in the physical environment. Results indicated that there were no interactions between prior knowledge and experimental condition. Students who learned with tablet PCs only outperformed students who additionally learned with real plants on a comprehension and an application test. In addition, high prior knowledge students outperformed low prior knowledge students on both tests. To investigate whether these effects were caused by the specific characteristics of the combination of photos of real plants and real plants, Experiment 2 compared the differential effects of prior knowledge on learning with the combination of texts, photos and real plants to a combination in which the photos were replaced by schematic hand drawings. Results indicated that both low and high prior knowledge students, who learned with the combination of texts, schematic hand drawings and real plants performed better on a comprehension and an application test. High prior knowledge students performed better on both tests. It is concluded that the number and type of representations used is critical for the effectiveness of mobile learning environments.     

Increasing urea-N efficiency for transplanted lowland rice by pneumatic injection: Yield and economics at the farm level

To increase the fertilizer-N efficiency in lowland rice (Oryza sativa L.) cultivation, new management practices are needed. Main cause of the present low efficiency is the low N recovery by plants, as a considerable part of the N applied is lost; deep placement techniques improve the recovery. A pneumatic injector, with which urea prills can be point-placed at a depth of 5–10 cm in paddy soils, was tested in 38 on-farm trials in 1989/90, mostly during the wet season. The experiments, located in Africa and Asia, focussed on differences in grain yield between conventional methods of broadcasting urea and injection by the pneumatic injector, at recommended N-rates. The study shows that the pneumatic injector is effective as a tool to improve the N fertilizer efficiency. The average yield increases per region, resulting from the use of the injector, ranged from about 250 to 1300 kg grain ha^–1. The value of the yield increase would allow most farmers to recover the costs of the injector within one season, even if labour was hired to carry out the injections. The average labour requirement of the injector was 40 hours ha^–1. In Indonesia, injection of prilled urea gave yields similar to those obtained with urea briquettes.