摘要：本文给出一种量子粒子群(QPSO)算法、改进菌群觅食(Ibfo)算法优化反向传播神经网络(BPNN)的混凝投药预测模型,利用量子粒子群的个体极值与群体极值更新细菌觅食算法趋化过程中细菌位置;通过细菌协同改进趋化算子提高优化精度,结合差分算法改进繁殖算子解决部分维度退化问题,加入轮盘赌方法作为选择机制改进迁移算子来克服优化过程中优秀解消失的缺陷;进而优化BP神经网络的权值、阈值以此预测混凝剂投药量.对云南某自来水厂的数据进行离线训练和模型测试,结果表明,所提算法预测结果的均方误差(MSE)达0.0116mg/L,平均绝对误差百分比(MAPE)达1.36%,在预测精度和稳定性上优于bfo-BPNN、PSO-BPNN等模型.

摘要：The oxides with perovskite structure possess abundant physical properties, such as magnetism, dielectricity, photoelectricity, ferroelectricity, etc. The oxygen ions in the perovskite unit cell constitute an octahedral distribution. The deformation or tilting of the special oxygen octahedra structure leads to new performances or properties change. Here, we give a review of the relationship between magnetic and electrical behaviors and oxygen octahedral tilting in several typical perovskite oxides. An understanding of how to tune these properties by controlling the tilting during the sample growth can more effectively guide the design of new structures for high performance and inspiring their potential applications.

摘要：In recent decades, magnetoelectric effect in multiferroic materials has attracted extensive attention owing to the upcoming demands for new-generation multi-functional magnetoelectronic devices, such as transducer, sensor and so on. This gives people a strong push to explore the multiferroic materials with a reduced dimension and effective coupling between electric and magnetic orderings, especially at room temperature. Due to the weak magnetoelectric coupling strength in sing-phase multiferroic materials, scientists start to design nanocomposites and artificial nanostructures with strong coupling among order parameters(lattice, charge, spin and orbital). In this review, we will introduce recent major progresses of magnetoelectric coupling in multiferroic nanocomposites across their interfaces from the following four aspects: strain effect, charge transfer, magnetic exchange interaction and orbital hybridization, based on their coupling mechanisms. Through a full understanding of the above coupling among these orderings, it is possible to achieve the nanoscale modulation of magnetization(ferroelectric polarization) by external electric(magnetic) field. Apart from the magnetoelectric coupling, those artificially functional nanocomposites provide us a platform to explore and study the emerging physical phenomena so that we can design self-assembled nanostructures to tailor novel functionalities in future applications.

摘要：Trial and error method can be used to find a suitable design of a fuzzy controller. However, there are many options including fuzzy rules, Membership Functions (MFs) and scaling factors to achieve a desired performance. An optimiza-tion algorithm facilitates this process and finds an optimal design to provide a desired performance. This paper presents a novel application of the Bacterial Foraging Optimization algorithm (bfo) to design a fuzzy controller for tracking control of a robot manipulator driven by permanent magnet DC motors. We use efficiently the bfo algorithm to form the rule base and MFs. The bfo algorithm is compared with a Particle Swarm Optimization algorithm (PSO). Performance of the controller in the joint space and in the Cartesian space is evaluated. Simulation results show superiority of the bfo algorithm to the PSO algorithm.

摘要：在众多多铁性化合物中,铁酸铋是目前已知唯一一种在室温下同时具有磁性和强铁电性的材料。近年来,纳米BiFeO3(bfo)材料常用于光催化领域研究,目前主要通过控制粒子大小和形状来提高其光催化性能,或掺杂各种金属元素以及设计相关复合材料等。本文从bfo纳米材料的制备工艺入手,综述了几种常见方法,包括溶胶-凝胶法、水热法、共沉淀法。总结了铁酸铋光催化剂的性能改进方式及其研究进展。