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Oil and gas well production prediction takes place in early stages of production to estimate future recovery. A data driven workflow is proposed in this paper to construct a symbolic tree model to predict new well production using historic time-series production data of analogous wells. Production data are firstly aggregated and symbolized for dimensionality reduction and data discretization of time-series...
Metabolic engineering is increasingly being used for the production of industrial products such as pharmaceuticals and enzymes. These chemicals have traditionally been chemically synthesized, but the application of synthetic biology techniques to microbes facilitates faster, cheaper production. Modelling and the integration of existing data can help inform the design of synthetic pathways. We applied...
We report preliminary results of an extensive investigation of theoretical and semi-empirical calculations of electron impact ionization cross sections, detailed by individual shells: they encompass the well known tabulations of the EEDL data library (also distributed within ENDF/B-VII) used by Geant4, MCNP and other codes, recent calculations used in Penelope, as well as other models not yet used...
Increasing efficiency of fatigue testing complex technical systems (for example, aircraft engine) is possible with its technical and economic assessment on base of relationship with the economic effect from the system operation. The amount of data is received during the engine life cycle. It should be properly processed to build the lifecycle model. Big Data concept can be suggested as an effective...
In recent years economic an social activity fields is based on data. Oil and gas industry leaders understand the value of big data and are interested in digital oil industry becoming a reality. Here is big data is analysed as a key component in based decision making in oil and gas industry during exploration, drilling and production. In oil and gas industry architectural model is offered for integration...
This paper presents the electrical power prediction based on the oscillating buoy wave energy converter which includes output power, annual electricity production and energy conversion efficiency. It is helpful to the performance test of the device and contributes to the dispatch control of the complex power and the study of the stability of the local power grid. To derive the prediction models, it...
Data-driven research is increasingly ubiquitous and data itself is a defining asset for researchers, particularly in the computational social sciences and humanities. Entire careers and research communities are built around valuable, proprietary or sensitive datasets. However, many existing computation resources fail to support secure and cost-effective storage of data while also enabling secure and...
Indian agriculture is a toughest profession with the unpredictability of climate and weather conditions that occur every year. India recently launched INSAT 3DR, an ISRO satellite which gives a clear picture of forecasting rainfall and weather conditions to improve its support to millions of Farmers. Although these facilities are available, the crop yield in affected by the unpredicted diseases which...
For many industrial production processes obeying certain statistical laws, a new method of establishing a SISO control model is put forward based on pattern recognition technology. Firstly, k-means clustering algorithm is used to partition input and output data collected into several classes respectively. Secondly, the distance between two classes is described by the distance of the two class centers...
This paper proposes methods for the development of mathematical models and for the control of operation modes of technological objects in oil refinery in face of uncertainty based on fuzzy information. The mathematical formulation of the problem of decision-making on controlling modes, which are solved on the basis of mathematical modeling, is formalized and obtained. By using the example of the problem...
To achieve both the aims of economic development and environment protection, environmental protection industry emerged. Its timely significance attracted great attention. This paper will take Suzhou as an example to analyze the developing situation of environment protection industry from 2007 to 2013 in China. Firstly, it is divided into four parts. Then, grey system model (GM(1,1) model) is used...
This extended abstract provides the scope of the semi-plenary lecture. A fault diagnosis system for a wind turbine typically has a modular structure, each module being dedicated to specific components or to performance monitoring. Important issues arising in the application of model-based fault diagnosis in an industrial context are discussed and illustrated on a performance monitoring module based...
Modularization is considered as one enabler for flexible and highly reconfigurable process plants. These characteristics are needed to overcome deficiencies regarding market volatility and shorter product innovation cycles. Current standardization activities aim at the specification of Module Type Package (MTP) files as a semantic description of modules for fast and efficient integration into process...
Todays production processes are becoming more and more flexible. Customers frequently demand specific production steps that fit to their processes. This leads to a needed flexibility for systems that are used to support decision making processes and the production itself. In this paper an approach is presented that uses process definition coming from an integrated enterprise modelling for connecting...
A method to define a best case behavioral or “golden inverter” software model has been developed, derived from either internal inverter readings (internal), high precision site based measurements or laboratory characterization and well defined conditions. The paper describes the method of the model development as well as the performance of the model for a selected use case.
Modern manufacturing systems based on cyber-physical systems with a growing amount of software allow frequent updates and reconfigurations to adapt the systems to volatile usage scenarios in the production. A diverse system environment arises even for similar or equal subsystems based on the same platform used at different locations. A major challenge for such systems is the regression test after...
Today's highly increasing product diversity and decreasing product life cycles, also in the automotive industry lead to fast changing production systems with a high ratio of mechatronic components and (control) software. That again leads to ever increasing use of Virtual Commissioning during the development process of automated manufacturing plants. Paired with the still increasing request towards...
This paper describes a wind and solar power production model for Europe based on the numerical weather prediction model COSMO-EU. The COSMO-EU model has hourly time resolution and a spatial resolution of 7 km × 7 km for Europe. The model is validated against power production information from the system operators in Denmark, Germany and Spain. Mean Average Error (MAE) (hourly error averaged for a year)...
Mycobacterium tuberculosis is a global health concern, causing over one million deaths a year. Alveolar macrophages, as the primary host cell of this intracellular bacterium, play an important role in the course of disease. Vitamin D3 is known to have a potent effect on macrophage behavior during infection, modulating the production of pro- and anti-inflammatory cytokines and immune effector molecules...
This paper presents modelling of a post-combustion CO2 capture process using bootstrap aggregated extreme learning machine. Extreme learning machine (ELM) randomly assigns the weights between input and hidden layers and obtains the weights between the hidden layer and output layer using regression type approach in one step. This paper proposes using principal component regression to obtain the weights...
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