Training and optimization of an artificial neural network controlling a hybrid power filter

A hybrid power compensator (HPC) consisting of a static VAr compensator and a dynamic compensator needs to be optimally controlled during the compensation of nonlinear loads. The HPC must be controlled to meet minimum requirements in terms of power factor and harmonic distortion, while at the same time minimizing its total cost. An artificial neural network (ANN) is used to control the HPC amidst a very dynamic power system environment. The performance of a reference ANN is evaluated while controlling an HPC connected to a typical nonlinear industrial load. The training and performance of the ANN is then optimized in terms of training set size, training set packing and ANN topology and the performance compared to the reference ANN. This paper highlights the importance of optimising the mentioned ANN parameters to achieve optimum ANN training and modeling accuracy. The results obtained reveals that the application of an ANN in controlling an HPC is feasible given that the ANN parameters are chosen appropriately.     

Bio-layer management in anaerobic membrane bioreactors for wastewater treatment.

Membrane separation technology represents an alternative way to achieve biomass retention in anaerobic bioreactors for wastewater treatment. Due to high biomass concentrations of anaerobic reactors, cake formation is likely to represent a major cause of flux decline. In the presented research, experiments are performed on the effect of biomass concentration and level of gas sparging on the hydraulic capacity of a submerged anaerobic membrane bioreactor. Both parameters significantly affected the hydraulic capacity, with biomass exerting the most pronounced effect. After 50 days of continuous operation the critical flux remained virtually unchanged, despite an increase in membrane resistance, suggesting that biomass characteristics and hydraulic conditions determine the bio-layer formation rather than the membrane's fouling level. The concept of bio-layer management is introduced to describe the programmed combination of actions performed in order to control the formation of biomass layer over membranes.     

Evaluating the impact of CASE: an empirical comparison of retrospective and cross-sectional survey approaches

The purpose of this paper is to evaluate two methods of assessing the productivity and quality impact of Computer Aided Software Engineering (CASE) and Fourth Generation Language (4GL) technologies: (1) by the retrospective method; and (2) the cross-sectional method. Both methods involve the use of questionnaire surveys. Developers' perceptions depend on the context in which they are expressed and this includes expectations about the effectiveness of a given software product. Consequently, it is generally not reliable to base inferences about the relative merits of CASE and 4GLs on a cross-sectional comparison of two separate samples of users. The retrospective method that requires each respondent to directly compare different products is shown to be more reliable. However, there may be scope to employ cross-sectional comparisons of the findings from different samples where both sets of respondents use the same reference point for their judgements, and where numerical rather than verbal rating scales are used to measure perceptions.     

The organisational learning effects of management accounting information under advanced manufacturing technology

This study empirically examined the organisational learning effects of the nonfinancial performance information provided by management accounting information systems (MAISs) under advanced manufacturing technology (AMT). In this study, a target costing system and the frequent and quick reporting of information were considered the facilitators of learning. First, we examined the relationships between AMT level and the amount of nonfinancial performance information produced by MAISs. The empirical results showed that there are significant positive relationships between the level of AMT and nonfinancial performance information. With a systems approach, we also proved the impact of the relationships among AMT levels, nonfinancial performance information and learning facilitators on the organisational performance of a firm. The results of our research suggest that under a high level of AMT, for the provision of information to result in an increase of performance through organisational learning, a target costing system must be introduced and a large amount of information should be provided frequently and quickly. The results of this study also showed that although AMT level may be low, fairly well-arranged facilitators and a moderately large amount of information may be necessary for the improvement of performance. In conclusion, effective organisational learning depends on the provision of relevant information as well as efficient learning support mechanisms.     

An Analysis of Scheduling Policies In Multiechelon Production Systems

Results of a simulation study of the economics of frequency of rescheduling Material Requirements Planning (MRP) systems are presented for a single-product, two-stage system in which demand is uncertain. The results indicate that for systems with moderate demand uncertainty, frequent rescheduling to maintain customer service may be uneconomical when compared with the alternative of more stable schedules in conjunction with safety stock. This result arises primarily because the cost of “emergency” production setups which occur when rescheduling is frequent exceeds the cost of safety stock required to “protect” stable schedules.     

智能化使汽车更安全

新的特性必须更加智能,在增加价值的同时不会分散驾驶者的注意力和增加事故的风险。