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Data and model Data sources and processing.
Historical data include construction value added and energy (fossil fuels listed in Table 1) end-use of the seven regions in East China from 2000 to 2010, sourced from [5][6] and [7] over the years.
Construction value added of each regions in 2020 are predicted with Grey Prediction Model GM(1,1) based on historical data[8].
Especially Shandong would become the focus of emission reduction in East China, since the proportion of its CO2 intensity reduction was close to 60%.
The Preferring potential case stimulates decision makers take differences among regions’ emission reduction space into account, and expect provinces with more reduction space to undertake greater reduction burden.

IT equipment and systems, housed in data centres, consume a considerable amount of energy.
In this paper, a numerical analysis of flow and temperature distribution of a raised-floor data centre is conducted in order to evaluate the thermal performance of the data centre.
The lower the SHI, the better the performance of the data centres.
As discussed by Fakhim et al. [6], data centre airspace can be divided into two main zones: data centre environment airspace excluding racks (AE), and airflow inside the racks (AR).
It is concluded that CRAC layout in model 11 to achieve an optimum performance in a medium data centre and model 6 leads to a worst performance of the data centre.

Before commencing rule discovery, several data mining pre-processing tools are applied to reduce data complexity and controversy as well.
The figure corresponds to sampling rate used in the data acquisition.
To avoid excessive learning time, redundant samples were removed using a cluster-based data reduction method.
We note that the data reduction task was conducted separately for each of the histories.
Of the 393 filtered samples (i.e. outputs of k-means data reduction method), 209 were low damage segments and 184 were high damage segments.

The kinetics of reduction of tungsten oxide has also been proposed.
Steps are as follows: Step 1: Removal of ammonia and crystallised water Theoretical Data: 11.17 % loss in weight when heated above 4500C [24] Observation: When heated above 4500C, 11.5% loss in weight Step 2: Reduction of tungsten oxide WO3 + 3H2 W + 3H2O (7) Given: Weight of the sample taken = 2 gm 1.
Beyond 45 minutes, the increase of percentage reduction was higher and at 10000C, rapid increase in the reduction to 99.9% was observed.
For 0.1 lpm, the percentage reduction in 60 minutes was 63.88%, whereas for 0.3 lpm the percentage reduction of 100% was obtained in 60 minutes time.
Table 1 Rate of reduction of APT with time S.No.

Research of Aluminum Reduction Cell Thermal Balanced Intelligent Control System Xiangyang Xia1,a, Jie Li1,b 1 School of Metallurgical Science and Engineering, Central South University, Changsha, Hunan, 410083, China axia_xy@126.com, bsummer719@sohu.com Keywords: aluminum reduction, control system, liquidus temperature, superheat, energy saving.
This control system can reduce the superheat of aluminum reduction cell in a certain range, and reduce production cost of per ton of primary aluminum on maximal degree.
Aluminum Reduction Cell Heat Balance Intelligent Control System Aluminum reduction cell heat balance intelligent control system Schematic was shown in figure 1.
Compared with the previous control system of aluminum reduction cells, the intelligent control system achieves the automatic temperature aluminum reduction cell temperature control, mainly through the sliding mode controller and repetitive controller.
According to the upper computer software to determine the electrolyte temperature and time curve between two points under the electrolyte temperature curve before and after the formation of a straight line, determined in a straight line on the left and the farthest point from the line point and the liquidus temperature to be marked and stored data generation report.

With the use of the kinetic analysis the optimal conditions were defined for the carbon thermal reduction as well as the initial data for the development of the joint carbon thermal reduction processes of zinc and iron oxides.
The data obtained through the industrial testing confirms the appropriateness of the process implementation and allows the cost effectiveness analysis of the zinc containing dust reclaiming.
According to the plant data the zinc content in the blast furnace slurries is 1 – 3 %, and in electric steelmaking slurries - 5 – 20 %.
This allowed obtaining the preliminary data required for the scaled-up experiments with the pellets at the lowest material cost.
To calculate the mass ratio of the initial and roasted samples the chemical analysis data on the total iron content was used as it is of high accuracy, and the iron at the reduction processes changes its valency but does not escape from the material.

What’s more, by comparing 10 common kinds of data mining algorithms in our experiment, we have analyzed and summarized that data preprocessing plays a vital role on the performance and importance to data mining algorithms.
b) data distribution is uneven L.
Data preprocessing This paper aims to explain the importance of data preprocessing and how to preprocess KDD Cup 99 dataset, the purpose is not to list all of the data preprocessing techniques.
Data preprocessing aims to improve the quality of dataset by employing any methods which can achieve this purpose, such as dimensionality reduction, normalization and other measures.
PCA is the most commonly used linear dimensionality reduction method, its goal is to map high-dimensional data space to low-dimensional representation by linear projection, and expect the greatest variance in the dimension of the projection data, in order to use fewer features to represent original features.

In this extremely complex weak system, numerous oxidation-reduction couples’ electronic exchange rate on the electrode is slow; therefore, establishing equilibrium potential is slow.
Results and discussion Computer recorded the ORP (accurate to 0.1mV) and temperature (accurate to 0.1℃) indication during the experiment, with 1s sampling time, making ORP (mV)-t(s) diagram, as shown in Figure 2: Fig.2 The curve between seawater ORP (mV) of salinity 5,20,30,35,40 and time(s) During the measurement process, the temperature was controlled at about 25.0℃, continuous measurement time of seawater of five different salinity was controlled at almost 65000s, or about 16h30min, which won more than 30 million online monitoring data.
The results are shown in Table 1: Table 1 Range of the equilibrium value and the equilibrium time for seawater ORP of different salinity salinity average（mV） range of the equilibrium value（mV） the beginning moment of the equilibrium value the ending moment of the equilibrium value the equilibrium time of the equilibrium value 5 237.1 234.9—239.3 820s/0.23h 45030s/12.51h 44210s/12.28h 20 231.2 229.0—233.4 4580s/1.27h 47700s/13.25h 43120s/11.98h 30 231.3 229.1—233.5 7120s/1.98h 50830s/14.12h 43710s/12.14h 35 236.4 234.2—238.6 14630s/4.06h 59400s/16.50h 44770s/12.44h 40 234.3 232.1—236.5 18000s/5.00h 65520s/18.20h 47520s/13.20h From the measured data listed on the above table, though, the five salinity of the seawater have a large gap, the difference among the ORP values were all less than 6.0mV.
The data above has fully demonstrated the tremendous impact of seawater salinity on equilibrium time of the ORP values, mainly due to the more the charged ions in seawater, the stronger the attraction between ions, the more difficult to form a stable force, the longer required time to achieve ORP stable values.
[2] Determination of oxidation-reduction potential (Electrometric method), SL94-1994(1995).

Many enterprises have strengthened the management and technique innovation of energy saving and emission reduction to improve the performance of energy conservation and emissions reduction.
Index weights were determined by both subjective and objective method, which fully considers the experience of experts and objective information of data.
Meanwhile, the energy saving and emission reduction target and relevant requirement of government should be considered, so that it can reflect progress of energy saving and emission reduction in thermal power enterprise prominently, effectively and comprehensively.
According to the measured data of evaluation index of energy saving and emission reduction in thermal power, the matter-element to be evaluated can be built.
And the performance level of energy saving and emission reduction in this plant project belongs to ‘high’level.

They recognized that the reduction of chromium oxide involves three independent stages: (i) reduction of Cr 3+ to Cr, (ii) formation of Cr 2+ either from the oxidation of Cr or the reduction of Cr 3+ and (iii) the reduction of Cr 2+ to Cr.
On the other hand, investigations on the thermodynamic equilibrium of liquid Fe - Cr alloys [4 - 8] have revealed more accurate data on the activities and free energies of formation of the constituents of the Fe - Cr system [4].
We now proceed to estimate the mass transfer coefficients from our experimental data.
Firstly, from the chromium concentration in the steel data, we calculate the number of moles of chromium that have been reduced in every time step.
The mass transfer coefficients for the reduction of chromium were estimated from experimental data.