This paper introduces the characteristics of TD-SCDMA, and analyzes some networking schemes and methods of multifrequency. For the 5 MHz frequency bandwidth, a frequency planning scheme containing three frequencies is...This paper introduces the characteristics of TD-SCDMA, and analyzes some networking schemes and methods of multifrequency. For the 5 MHz frequency bandwidth, a frequency planning scheme containing three frequencies is examined, and a simulation model is built to validate the performance of this scheme. Finally, this paper analyzes the advantages and disadvantages of the scheme, and proposes some directions for the future study of networking planning.展开更多
Being familiar with characteristics of industrial town effluents from various wastewater treatment units, which have high qualitative and quantitative variations and more uncertainties compared to urban wastewaters, p...Being familiar with characteristics of industrial town effluents from various wastewater treatment units, which have high qualitative and quantitative variations and more uncertainties compared to urban wastewaters, plays very effective role in governing them. With regard to environmental issues, proper operation of wastewater treatment plants is of par- ticular importance that in the case of inappropriate utilization, they will cause serious problems. Processes that exist in environmental systems mostly have two major characteristics: they are dependent on many variables;and there are complex relationships between its components which make them very difficult to analyze. In order to achieve a better and efficient control over the operation of an industrial wastewater treatment plant (WWTP), powerful mathematical tool can be used that is based on recorded data from some basic parameters of wastewater during a period of treatment plant operation. In this study, the treatment plant was divided into two main subsystems including: Low TDS (Total Dissolved Solids) treatment unit and Biological unit (extended aeration). The multilayer perceptron feed forward neural network with a hidden layer and stop training method was used to predict quality parameters of the industrial effluent. Data of this study are related to the Fajr Industrial Wastewater Treatment Plant, located in Mahshahr—Iran that qualita- tive and quantitative characteristics of its units were used for training, calibration and validation of the neural model. Also, Principal Component Analysis (PCA) technique was applied to improve performance of generated models of neural networks. The results of L-TDS unit showed good accuracy of the models in estimating qualitative profile of wastewater but results of biological unit did not have sufficient accuracy to being used. This model facilitates evaluating the performance of each treatment plant units through comparing the results of prediction model with the standard amount of outputs.展开更多
Nowadays, with regard to environmental issues, proper operation of wastewater treatment plants is of particular importance that in the case of inappropriate utilization, they will cause serious problems. Processes tha...Nowadays, with regard to environmental issues, proper operation of wastewater treatment plants is of particular importance that in the case of inappropriate utilization, they will cause serious problems. Processes that exist in environmental systems and environmental engineers are dealing with them mostly have two major characteristics: they are dependent on many variables;and there are complex relationships between its components which make them very difficult to analyze. Being familiar with characteristics of industrial town effluents from various wastewater treatment units, which have high qualitative and quantitative variations and more uncertainties compared to urban wastewaters, plays very effective role in governing them. In order to achieve a better and efficient control over the operation of an industrial wastewater treatment plant, powerful mathematical tool can be used that is based on recorded data from some basic parameters of wastewater during a period of treatment plant operation. In this study, the multilayer perceptron (MLP) feed forward neural network with a hidden layer and stop training method was used to predict quality parameters of the industrial effluent. Data of this study are related to the Fajr Industrial Wastewater Treatment Plant located in Mahshahr—Iran that qualitative and quantitative characteristics of its units were used for training, calibration and evaluation of the neural model. Also, Principal Component Analysis technique was applied to modify and improve performance of generated models of neural networks. The results of this model showed good accuracy of the model in estimating qualitative pro- file of wastewater. This model facilitates evaluating the performance of each treatment plant units through comparing the results of prediction model with the standard amount of output.展开更多
为了有效地扩大基站无线覆盖范围,吸收更多的用户和话务量,降低建设成本,提高收益,实现科学的基站选址,提出了一种适应于分时长期演进(time division long term evolution,TD-LTE)网络的高效的、智能的4G无线网络规划方法,通过综合考虑4...为了有效地扩大基站无线覆盖范围,吸收更多的用户和话务量,降低建设成本,提高收益,实现科学的基站选址,提出了一种适应于分时长期演进(time division long term evolution,TD-LTE)网络的高效的、智能的4G无线网络规划方法,通过综合考虑4G网络的同频干扰、正交频分复用(OFDM)、小区边缘速率、参考信号强度(RSRP)和基站站址密度等,建立一个以建设成本、覆盖率和容量为目标的多目标组合优化规划模型;并采用加入局部搜索的遗传算法进行智能求解。仿真结果表明该模型不但能够求出以最少的成本建设最大覆盖的网络方案,而且能够求出每个建设基站的天线类型、天线挂高和小区类型;同时加入局部搜索后的算法速度得到明显的提高。展开更多
针对电力无线通信在应用中存在的问题,为更好地服务智能电网和开展分时长期演进(time division long term evolution,TD-LTE)技术在电力通信等领域的应用研究,建立了TD-LTE电力无线专网仿真平台。从链路级仿真和系统级仿真两个方面对电...针对电力无线通信在应用中存在的问题,为更好地服务智能电网和开展分时长期演进(time division long term evolution,TD-LTE)技术在电力通信等领域的应用研究,建立了TD-LTE电力无线专网仿真平台。从链路级仿真和系统级仿真两个方面对电力无线专网的性能进行仿真,并分析了无线参数对无线专网性能的影响。该仿真平台的建立为电力终端通信接入网的统一建设和LTE电力无线专网的应用提供技术支撑,也为后期的网络规划奠定了理论基础。展开更多
文摘This paper introduces the characteristics of TD-SCDMA, and analyzes some networking schemes and methods of multifrequency. For the 5 MHz frequency bandwidth, a frequency planning scheme containing three frequencies is examined, and a simulation model is built to validate the performance of this scheme. Finally, this paper analyzes the advantages and disadvantages of the scheme, and proposes some directions for the future study of networking planning.
文摘Being familiar with characteristics of industrial town effluents from various wastewater treatment units, which have high qualitative and quantitative variations and more uncertainties compared to urban wastewaters, plays very effective role in governing them. With regard to environmental issues, proper operation of wastewater treatment plants is of par- ticular importance that in the case of inappropriate utilization, they will cause serious problems. Processes that exist in environmental systems mostly have two major characteristics: they are dependent on many variables;and there are complex relationships between its components which make them very difficult to analyze. In order to achieve a better and efficient control over the operation of an industrial wastewater treatment plant (WWTP), powerful mathematical tool can be used that is based on recorded data from some basic parameters of wastewater during a period of treatment plant operation. In this study, the treatment plant was divided into two main subsystems including: Low TDS (Total Dissolved Solids) treatment unit and Biological unit (extended aeration). The multilayer perceptron feed forward neural network with a hidden layer and stop training method was used to predict quality parameters of the industrial effluent. Data of this study are related to the Fajr Industrial Wastewater Treatment Plant, located in Mahshahr—Iran that qualita- tive and quantitative characteristics of its units were used for training, calibration and validation of the neural model. Also, Principal Component Analysis (PCA) technique was applied to improve performance of generated models of neural networks. The results of L-TDS unit showed good accuracy of the models in estimating qualitative profile of wastewater but results of biological unit did not have sufficient accuracy to being used. This model facilitates evaluating the performance of each treatment plant units through comparing the results of prediction model with the standard amount of outputs.
文摘Nowadays, with regard to environmental issues, proper operation of wastewater treatment plants is of particular importance that in the case of inappropriate utilization, they will cause serious problems. Processes that exist in environmental systems and environmental engineers are dealing with them mostly have two major characteristics: they are dependent on many variables;and there are complex relationships between its components which make them very difficult to analyze. Being familiar with characteristics of industrial town effluents from various wastewater treatment units, which have high qualitative and quantitative variations and more uncertainties compared to urban wastewaters, plays very effective role in governing them. In order to achieve a better and efficient control over the operation of an industrial wastewater treatment plant, powerful mathematical tool can be used that is based on recorded data from some basic parameters of wastewater during a period of treatment plant operation. In this study, the multilayer perceptron (MLP) feed forward neural network with a hidden layer and stop training method was used to predict quality parameters of the industrial effluent. Data of this study are related to the Fajr Industrial Wastewater Treatment Plant located in Mahshahr—Iran that qualitative and quantitative characteristics of its units were used for training, calibration and evaluation of the neural model. Also, Principal Component Analysis technique was applied to modify and improve performance of generated models of neural networks. The results of this model showed good accuracy of the model in estimating qualitative pro- file of wastewater. This model facilitates evaluating the performance of each treatment plant units through comparing the results of prediction model with the standard amount of output.
文摘为了有效地扩大基站无线覆盖范围,吸收更多的用户和话务量,降低建设成本,提高收益,实现科学的基站选址,提出了一种适应于分时长期演进(time division long term evolution,TD-LTE)网络的高效的、智能的4G无线网络规划方法,通过综合考虑4G网络的同频干扰、正交频分复用(OFDM)、小区边缘速率、参考信号强度(RSRP)和基站站址密度等,建立一个以建设成本、覆盖率和容量为目标的多目标组合优化规划模型;并采用加入局部搜索的遗传算法进行智能求解。仿真结果表明该模型不但能够求出以最少的成本建设最大覆盖的网络方案,而且能够求出每个建设基站的天线类型、天线挂高和小区类型;同时加入局部搜索后的算法速度得到明显的提高。
文摘针对电力无线通信在应用中存在的问题,为更好地服务智能电网和开展分时长期演进(time division long term evolution,TD-LTE)技术在电力通信等领域的应用研究,建立了TD-LTE电力无线专网仿真平台。从链路级仿真和系统级仿真两个方面对电力无线专网的性能进行仿真,并分析了无线参数对无线专网性能的影响。该仿真平台的建立为电力终端通信接入网的统一建设和LTE电力无线专网的应用提供技术支撑,也为后期的网络规划奠定了理论基础。
