This article deals with the design of energy efficient water utilization systems allowing operation split. Practical features such as operating flexibility and capital cost have made the number of sub operations an im...This article deals with the design of energy efficient water utilization systems allowing operation split. Practical features such as operating flexibility and capital cost have made the number of sub operations an important parameter of the problem. By treating the direct and indirect heat transfers separately, target freshwater and energy consumption as well as the operation split conditions are first obtained. Subsequently, a mixed integer non-linear programming （MINLP） model is established for the design of water network and the heat exchanger network （HEN）. The proposed systematic approach is limited to a single contaminant. Example from literature is used to illustrate the applicability of the approach.展开更多
A new approach, named TCP-I2NC, is proposed to improve the interaction between network coding and TCP and to maximize the network utility in interference-free multi-radio multi-channel wireless mesh networks. It is gr...A new approach, named TCP-I2NC, is proposed to improve the interaction between network coding and TCP and to maximize the network utility in interference-free multi-radio multi-channel wireless mesh networks. It is grounded on a Network Utility Maxmization (NUM) formulation which can be decomposed into a rate control problem and a packet scheduling problem. The solutions to these two problems perform resource allocation among different flows. Simulations demonstrate that TCP-I2NC results in a significant throughput gain and a small delay jitter. Network resource is fairly allocated via the solution to the NUM problem and the whole system also runs stably. Moreover, TCP-I2NC is compatible with traditional TCP variants.展开更多
Recent trends in environmental management of water resource have enlarged the demand for predicting techniques that can provide reliable, efficient and accurate water quality. In this case study, the authors applied t...Recent trends in environmental management of water resource have enlarged the demand for predicting techniques that can provide reliable, efficient and accurate water quality. In this case study, the authors applied the Artificial Neural Networks （ANN） to estimate the water quality index on the Dong Nai River flowing through Dong Nai and Binh Duong provinces. The information and data including 10 water quality parameters of the Dong Nai River at 23 monitoring stations were collected during the recorded time period from 2010 to 2014 to build water quality prediction models. The results of the study demonstrated that the Water Quality Index （WQI） forecasted with GRNN was very significant and had high correlation coefficient （R2 = 0.974 and p = 0.0） compared to the real values of the WQI. Moreover, the ANN models provided better predicted values than the multiple regression models did.展开更多
ANNs （Artificial neural networks） are used extensively in remote sensing image processing. It has been proven that BPNNs （back-propagation neural networks） have high attainable classification accuracy. However, th...ANNs （Artificial neural networks） are used extensively in remote sensing image processing. It has been proven that BPNNs （back-propagation neural networks） have high attainable classification accuracy. However, there is a noticeable variation in the achieved accuracies due to different network designs and implementations. Hence, researchers usually need to conduct several experimental trials before they can finalize the network design. This is a time consuming process which significantly reduces the effectiveness of using BPNNs and the final design may still not be optimal. Therefore, there is a need to see whether there are some common guidelines for effective design and implementation of BPNNs. With this aim in mind, this paper attempts to find and summarize the common guidelines suggested by different authors through literature review and discussion of the findings. To provide readers with background and contextual information, some ANN fundamentals are also introduced.展开更多
On the basis of analysis and selection of factors influencing operation cost of coal resources development, fuzzy set method and artificial neural network (ANN) were adopted to set up the classification analysis model...On the basis of analysis and selection of factors influencing operation cost of coal resources development, fuzzy set method and artificial neural network (ANN) were adopted to set up the classification analysis model of coal resources. The collected samples were classified by using this model. Meanwhile, the pattern recognition model for classifying of the coal resources was built according to the factors influencing operation cost. Based on the results achieved above, in the light of the theory of information diffusion, the calculation model for operation cost of coal resources development has been presented and applied in practice, showing that these models are reasonable.展开更多
The highly-efficient dry separation technique using a gas-solid fluidized bed is very beneficial for increasing coal grade and optimizing the utilization of coal resources.The size distribution of the solid medium(e.g...The highly-efficient dry separation technique using a gas-solid fluidized bed is very beneficial for increasing coal grade and optimizing the utilization of coal resources.The size distribution of the solid medium(e.g.,magnetite powder) used in this technique is one of key factors that influences fluidization and separation performance.It is,therefore,urgent to prepare medium in a way that operates at low cost and high efficiency.Grinding experiments were performed using a planetary ball mill equipped with a frequency converter.The effect of fed mass,rotation frequency of the mill,grinding time and the ball-size ratio on grinding performance was investigated.The grinding parameters were optimized by numerical calculations using Artificial Neural Network(ANN) in Matlab.A regression equation for predicting the yield of the desired product(i.e.,0.3～0.15 mm magnetite powder) is proposed.The maximum yield of 0.3～0.15 mm particles was 47.24%.This lays a foundation for the industrial-scale production of the solid medium required for separation with a magnetite-powder fluidized bed.展开更多
基金Supported by the Major Project of National Natural Science Foundation of China （No.20409205） and National High Technology Research and Development Program of China （No.G20070040）.
文摘This article deals with the design of energy efficient water utilization systems allowing operation split. Practical features such as operating flexibility and capital cost have made the number of sub operations an important parameter of the problem. By treating the direct and indirect heat transfers separately, target freshwater and energy consumption as well as the operation split conditions are first obtained. Subsequently, a mixed integer non-linear programming （MINLP） model is established for the design of water network and the heat exchanger network （HEN）. The proposed systematic approach is limited to a single contaminant. Example from literature is used to illustrate the applicability of the approach.
基金This work was supported by the State Key Program of Na- tional Nature Science Foundation of China under Grants No. U0835003, No. 60872087.
文摘A new approach, named TCP-I2NC, is proposed to improve the interaction between network coding and TCP and to maximize the network utility in interference-free multi-radio multi-channel wireless mesh networks. It is grounded on a Network Utility Maxmization (NUM) formulation which can be decomposed into a rate control problem and a packet scheduling problem. The solutions to these two problems perform resource allocation among different flows. Simulations demonstrate that TCP-I2NC results in a significant throughput gain and a small delay jitter. Network resource is fairly allocated via the solution to the NUM problem and the whole system also runs stably. Moreover, TCP-I2NC is compatible with traditional TCP variants.
文摘Recent trends in environmental management of water resource have enlarged the demand for predicting techniques that can provide reliable, efficient and accurate water quality. In this case study, the authors applied the Artificial Neural Networks （ANN） to estimate the water quality index on the Dong Nai River flowing through Dong Nai and Binh Duong provinces. The information and data including 10 water quality parameters of the Dong Nai River at 23 monitoring stations were collected during the recorded time period from 2010 to 2014 to build water quality prediction models. The results of the study demonstrated that the Water Quality Index （WQI） forecasted with GRNN was very significant and had high correlation coefficient （R2 = 0.974 and p = 0.0） compared to the real values of the WQI. Moreover, the ANN models provided better predicted values than the multiple regression models did.
文摘ANNs （Artificial neural networks） are used extensively in remote sensing image processing. It has been proven that BPNNs （back-propagation neural networks） have high attainable classification accuracy. However, there is a noticeable variation in the achieved accuracies due to different network designs and implementations. Hence, researchers usually need to conduct several experimental trials before they can finalize the network design. This is a time consuming process which significantly reduces the effectiveness of using BPNNs and the final design may still not be optimal. Therefore, there is a need to see whether there are some common guidelines for effective design and implementation of BPNNs. With this aim in mind, this paper attempts to find and summarize the common guidelines suggested by different authors through literature review and discussion of the findings. To provide readers with background and contextual information, some ANN fundamentals are also introduced.
文摘On the basis of analysis and selection of factors influencing operation cost of coal resources development, fuzzy set method and artificial neural network (ANN) were adopted to set up the classification analysis model of coal resources. The collected samples were classified by using this model. Meanwhile, the pattern recognition model for classifying of the coal resources was built according to the factors influencing operation cost. Based on the results achieved above, in the light of the theory of information diffusion, the calculation model for operation cost of coal resources development has been presented and applied in practice, showing that these models are reasonable.
基金supported by the National Natural Science Foundation of China (Nos.50921002 and 90510002)the National High Technology Research and Development Program of China (No.2007AA05Z318)
文摘The highly-efficient dry separation technique using a gas-solid fluidized bed is very beneficial for increasing coal grade and optimizing the utilization of coal resources.The size distribution of the solid medium(e.g.,magnetite powder) used in this technique is one of key factors that influences fluidization and separation performance.It is,therefore,urgent to prepare medium in a way that operates at low cost and high efficiency.Grinding experiments were performed using a planetary ball mill equipped with a frequency converter.The effect of fed mass,rotation frequency of the mill,grinding time and the ball-size ratio on grinding performance was investigated.The grinding parameters were optimized by numerical calculations using Artificial Neural Network(ANN) in Matlab.A regression equation for predicting the yield of the desired product(i.e.,0.3～0.15 mm magnetite powder) is proposed.The maximum yield of 0.3～0.15 mm particles was 47.24%.This lays a foundation for the industrial-scale production of the solid medium required for separation with a magnetite-powder fluidized bed.
