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51.
Frontiers of Mechanical Engineering - In the process of cutting, the relative vibration between the cutter and the workpiece has an important effect on the surface topography. In this study, the... 相似文献
52.
《International Journal of Hydrogen Energy》2020,45(1):873-890
Mg–Fe Layered Double Hydroxide (LDH) with M2+: M3+ 3:1 stoichiometric ratio was synthesized and employed as catalyst precursor for COx-free hydrogen production from ammonia. The resulting catalyst showed good catalytic activity. A series of Mg/Co–Fe layered double hydroxides were synthesized by replacing Mg2+ with Co2+ without disturbing M2+:M3+ ratio. The influence of nature and extent of Co(II) substitution on structure, morphology and surface properties were studied. A systematic study was carried out using these materials as catalyst precursors for ammonia decomposition. BET, XRD, TPR, XPS, CO2-TPD and TEM techniques were used to characterize the synthesized catalysts. These Fe-based catalysts are highly active, highly stable and not promoting any stable surface nitridation during the ammonia decomposition reaction. Among all catalysts, the Mg3Co3Fe2 catalyst showed the highest activity i.e. 100% conversion at 6,000 h−1 and 60% at 50,000 h−1 space velocities at 550 °C. The registered superior catalytic activity was result of the formed specific catalyst's properties like high surface area, high surface Co and Fe atomic concentration and suitable basicity. These Fe-based materials are, cost-effective, easily synthesize and highly stable, thus attractive for large-scale operation. 相似文献
53.
The integration of planning and scheduling decisions in rigorous mathematical models usually results in large scale problems. In order to tackle the problem complexity, decomposition techniques based on duality and information flows between a master and a set of subproblems are widely applied. In this sense, ontologies improve information sharing and communication in enterprises and can even represent holistic mathematical models facilitating the use of analytic tools and providing higher flexibility for model building. In this work, we exploit this ontologies’ capability to address the optimal integration of planning and scheduling using a Lagrangian decomposition approach. Scheduling/planning sub-problems are created for each facility/supply chain entity and their dual solution information is shared by means of the ontological framework. Two case studies based on a STN representation of supply chain planning and scheduling models are presented to emphasize the advantages and limitations of the proposed approach. 相似文献
54.
55.
Optimal Pricing Algorithm in the Electricity Market with Battery and Accumulator and Demand–Supply Balancing 下载免费PDF全文
This paper considers the day‐ahead market with batteries and accumulators to level power generation. First, we model consumers with batteries, generators with batteries, and accumulators, all of whom strive to maximize their own profit. An optimal pricing algorithm based on dual decomposition and the steepest descent method is derived and shown to be stable. Finally, the effectiveness of the algorithm is demonstrated by means of numerical simulations which indicate that it achieves demand–supply balance. 相似文献
56.
一种广义不可分支持向量机算法 总被引:1,自引:1,他引:0
针对标准的C-SVM(C-support vector machine)算法在处理很多实际分类问题时,对识别错误代价损失差异很大的极端情况表现出的局限性,提出一种通用的
广义支持向量机算法。根据识别错误后所付出的代价,可以把最优分类面向代价损失低的一方进行推移,留给代价损失高的一方更大的空间,提高其识别率,从而减小识别错误后带来的代价损失。该方法进一步提高了标准C SVM的适用性以及样本的正确识别率,将新算法应用到高分辨雷达距离像的识别中,实验证明,广义C-SVM能取得比传统C-SVM更好的识别效果。 相似文献
57.
Human mobility prediction is of great advantage in route planning and schedule management. However, mobility data is a high-dimensional dataset in which multi-context prediction is difficult in a single model. Mobility data can usually be expressed as a home event, a work event, a shopping event and a traveling event. Previous works have only been able to learn and predict one type of mobility event and then integrate them. As the tensor model has a strong ability to describe high-dimensional information, we propose an algorithm to predict human mobility in tensors of location context data. Using the tensor decomposition method, we extract human mobility patterns with multiple expressions and then synthesize the future mobility event based on mobility patterns. The experiment is based on real-world location data and the results show that the tensor decomposition method has the highest accuracy in terms of prediction error among the three methods. The results also prove the feasibility of our multi-context prediction model. 相似文献
58.
In this research, we propose a novel framework referred to as collective game behavior decomposition where complex collective behavior is assumed to be generated by aggregation of several groups of agents following different strategies and complexity emerges from collaboration and competition of individuals. The strategy of an agent is modeled by certain simple game theory models with limited information. Genetic algorithms are used to obtain the optimal collective behavior decomposition based on history data. The trained model can be used for collective behavior prediction. For modeling individual behavior, two simple games, the minority game and mixed game are investigated in experiments on the real-world stock prices and foreign-exchange rate. Experimental results are presented to show the effectiveness of the new proposed model. 相似文献
59.
Model predictive control (MPC) has been effectively applied in process industries since the 1990s. Models in the form of closed equation sets are normally needed for MPC, but it is often difficult to obtain such formulations for large nonlinear systems. To extend nonlinear MPC (NMPC) application to nonlinear distributed parameter systems (DPS) with unknown dynamics, a data-driven model reduction-based approach is followed. The proper orthogonal decomposition (POD) method is first applied off-line to compute a set of basis functions. Then a series of artificial neural networks (ANNs) are trained to effectively compute POD time coefficients. NMPC, using sequential quadratic programming is then applied. The novelty of our methodology lies in the application of POD's highly efficient linear decomposition for the consequent conversion of any distributed multi-dimensional space-state model to a reduced 1-dimensional model, dependent only on time, which can be handled effectively as a black-box through ANNs. Hence we construct a paradigm, which allows the application of NMPC to complex nonlinear high-dimensional systems, even input/output systems, handled by black-box solvers, with significant computational efficiency. This paradigm combines elements of gain scheduling, NMPC, model reduction and ANN for effective control of nonlinear DPS. The stabilization/destabilization of a tubular reactor with recycle is used as an illustrative example to demonstrate the efficiency of our methodology. Case studies with inequality constraints are also presented. 相似文献
60.
In the paper two new locally one-dimensional alternating segment schemes for solving the 2-D parabolic problems are developed. The parabolic problems can be solved efficiently over decomposed sub-domains. Two schemes are proved to be unconditionally stable and numerical experiments show the validity of the schemes. 相似文献