本周，我关注着在纽约州约翰逊市进行的一项基于锂离子的储能网络研究。
This week, I’m reading about a lithium ion-based energy storage grid in Johnson City, N.Y.
现在，我们无时无刻不在通过互联网看新闻、听音乐、网购、看电视脱口秀节目甚至使用网络转储文件。
We now read the news, listen to music, shop, watch TV showsand store our files on the web.
利用人工神经网络储层预测技术，进行隐蔽油气藏预测，有成功的，也有失败的。
We have seen some successful and some failure examples for predicting the hidden reservoir with artificial neural networks reservoir prediction technique.
本文研究的主要目的是：以常规测井资料为基础，应用神经网络技术来识别火成岩储层中的油气水层。
The main purpose of this thesis is to identify oil and gas layers in the igneous reservoirs by using the neural network based on the common well logs.
应用表明，RBF神经网络在储层表征问题中有着广阔的应用前景。
The results show that the RBF neural network is very promising for the application of petroleum reservoir characterization.
但是，它们都存在着较大的误差，所以，本文中采用BP神经网络技术来识别火成岩储层的油气水层。
But they all produce the bigger error margin. So, BP neural network technique is made use of identifying the oil-gas-water layers in igneous reservoirs.
本文引入神经网络技术，用以研究碳酸盐岩测井信息与岩心分析孔隙度的关系，并由此预测储层孔隙度。
The relation between carbonate rock logging information and core analysis porosity is studied by neural net technique to forecast reservoir porosity in this paper.
用BP网络建立识别储集类型模型，识别结果与成像测井识别结果和岩心分析结果吻合。
The BP neural network based reservoir model provides the same result as that of FMI and core analysis.
针对电容储能高功率脉冲成形网络工作过程中存在的电流和电压冲击问题，建立了脉冲成形网络的等效电路。
Aiming at the current and voltage impulse problems in a high power pulse forming network with capacitor energy storage system, the equivalent circuit model of the pulse forming network is established.
针对河流-三角洲储层沉积微相划分问题，提出了一种基于加权模糊推理神经网络的判别方法。
Focusing on the classification of sedimentary microfacies in fluvial delta reservoir, one diagnosis based on weighted fuzzy neural network is proposed.
通过实际资料应用表明，在单独应用BP网络进行储层及油气预测效果较差的地区，采用模糊神经网络能取得较好的效果。
It has been shown in practical application that the fuzzy neural network brings good prediction effect in an area in which BP network has poor hydrocarbon prediction effect.
通过实例介绍了利用一种概率神经网络技术预测储层物性参数的方法。
Using an example, a method based on probabilistic neural network technique is introduced, which aims at prediction of petrophysical parameters for reservoir.
依靠分布式电源发电和带蓄电池储能系统的孤立网络在国际上得到了广泛的应用。
Stand alone system with the distributed generation and the battery energy storage system (BESS) is widely applied in the world.
针对河流-三角洲储层沉积微相的划分问题，提出了基于加权模糊推理神经网络的判别方法。
Based on the division of river-delta reservoir sedimentary facies, we present a distinguishing method based on the fuzzy reasoning NN.
神经网络油气模式识别技术可以作为东海地区储层油气预测的一种手段。
Therefore, the hydrocarbon pattern recognition of neural network may be considered as an effective tool to forecast reservoir oil and gas in East China Sea.
结论基于神经网络模型的井间参数预测方法，可以为储层精细评价提供高质量的油藏地质模型。
Conclusion The method of parameter predict can provide a high quality oil pool geological model for reservoir fine evaluation.
该储层具有裂缝-孔隙双重孔隙网络，常形成相对低电阻率油层。
The reservoirs often form the low contrast resistivity oil layers because they have the dual pore networks, that is, fractures and pores.
采用人工神经网络测井识别技术识别油层并进行储层物性及含油性的解释。
Therefore, it is very difficult to distinguish oil with water layer and to evaluate oil layer by using logging data.
利用这些地震属性参数，通过模糊神经网络的方法，对碳酸盐岩储层进行综合预测与评价。
The carbonate reservoir was predicted and evaluated comprehensively by using the method of fuzzy neural net according to these seismic attribute parameters.
采用BP神经网络技术计算煤层气储层物性参数和含气量，较好的满足了煤层气储量计算及开发部署对解释精度的要求。
Using BP neural network computing CBM reservoir parameters, gas content, it's better to meet the calculation of CBM reservoir and interpretation accuracy for development.
作者最后利用人工神经网络多属性反演得到全区的视电阻率和剩余电阻率曲线，主要用于油气检测，最终圈划出有利油气储集区，并找到有利油气圈闭高81东块。
It can predict any logs' curves such as resistivity log, so it could be used as detecting oil and gas. Finally we use the technique to find a favorable area rich in oil, and a trap, Gao81 east.
那便使亡储区域网络得到了建设和收铺。
This makes the StorageAreaNetwork get construction and development.
并设计了两种能量存储电路：电容储能电路和充电电池储能电路，对电能进行储存并为无线网络传感器供能。
Two kinds of energy storage circuit is designed: capacitor circuit and rechargeable battery circuit, through which electrical energy is supplied for wireless sensor networks.
提出了基于故障树信息、专家评价的模糊神经网络的风险评价方法，以焦炉煤气储配站系统为研究对象，对其进行了风险评价。
This paper advances an expert assessment method that is based upon the experts logical estimation for evaluating the investment risks of real estate exploitation .
提出了基于故障树信息、专家评价的模糊神经网络的风险评价方法，以焦炉煤气储配站系统为研究对象，对其进行了风险评价。
This paper advances an expert assessment method that is based upon the experts logical estimation for evaluating the investment risks of real estate exploitation .
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