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The study was done by analyzing wind resource data of the site for 2-years (2008 & 2009) at a height of 40 m and applying the extrapolated wind speed resource at 70m height on four different wind turbine models – Suzlon S66, Gamesa G80, HeWind HW77 and RE Power MM82.
The RETScreen feasibility study report of the 30 MW wind power plant for Bony Island are discussed in section 4.3 to 4.6. 4.2 Climate Data Table 5: Climatic Data of Bonny Island (Source: RETScreen) Month Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Average Air Temp. (0C) 27.5 28.7 28.0 27.9 27.4 26.3 25.6 25.3 25.5 26.3 27.0 26.7 26.8 Wind speed (m/s) 2.6 4.3 5.0 4.3 4.4 4.8 4.4 5.4 4.3 4.0 3.9 3.7 4.3 Relative Humidity (%) 78.6 80.8 86.2 88.9 89.9 90.4 90.2 89.8 90.7 90.8 88.1 81.3 87.2 4.3 Discussion on Annual Energy Production This analysis was prepared using the RETScreen Energy Management Software.
Table 6a: Financial Viability of 30 MW Power Plant in Bonny Island Financial parameters Unit Inflation rate 2 % Discount rate 9 % Project life 20-years Dept ratio 70 % Debt $ 44,100,000 Equity $ 18,900,000 Dept interest rate 10 % Debt term 10-years Debt payment $ 7,177,072 /year Table 6b: Annual Revenue of a 30 MW Power Plant in Bonny Island Annual Revenue Unit Electricity export to grid 89,684 MWh Electricity export rate 0.1 $/ kWh Electricity export revenue $ 8, 968, 404 Net GHG reduction 38,757 tCO2 /year Net GHG reduction – 20 years 771, 143 tCO2 GHG reduction credit rate $ 40/ tCO2 GHG reduction revenue $ 1,550,286 GHG reduction credit duration 20-years GHG reduction credit escalation rate 2 % From the financial report, the annual revenue generated from electricity export is $8,968,404 with an additional GHG saving of $1,550,286; while the debt payment amounted to $7,177,072.
The RETSCREEN feasibility analysis was carried out based on two years wind speed data, to assess the viability of wind power generation potential for Bonny Island.
[17] Enercon report, 2019 [18] Emmanuel Yeboah Osei, Eric Osei Essandoh, “RETScreen Assessment of Utility Scale Wind Power Generation Based on Historical Wind Speed Data-the Case of Mankoadze in the Central Region of Ghana”, Research Journal of Applied Sciences, Engineering and Technology, vol.7(21), pp. 4593-4600, June 2014.

The possibility of using lattice periodic functions in the processing of narrowband signals with methods of discrete Fourier transform, instantaneous spectral density, and synchronous detection providing reduction of the number of readouts being processed, is shown.
Initial data of test example Harmonic component no.
The results of calculations of the test example Method The number of readouts, N Frequency , Hz Amplitude value V Phase angle j, degree Classic ISD 100000 50.0 200.0000 45.0000 50.1 200.5000 83.0000 50.2 200.3000 0.0000 for 2000 50.0 200.0000 45.0000 2004 50.1 200.5000 83.0000 2008 50.2 200.3000 0.0000 for 2500 50.0 200.0000 45.0000 2505 50.1 200.5000 83.0000 2510 50.2 200.3000 0.0000 for 3000 50.0 200.000 45.0000 3006 50.1 200.5000 83.0000 3012 50.2 200.3000 0.0000 for 3500 50.0 200.0021 44.7366 3507 50.1 200.498 82.9999 3514 50.2 200.2954 0.0000 for 4000 50.0 200.0000 45.0000 4008 50.1 200.5000 83.0000 4016 50.2 200.3000 0.0000 According to the experimental results it can be stated that the method being considered provides reduction of the number of readouts being processed, and, as a consequence, reduces span time required for calculation of the spectral portrait.
Summary In conclusion of review of possible ways of using lattice periodic functions in calculation of spectral portraits of narrow band periodic signals we note again a significant reduction of the number of readouts being processed. 

Fatigue tests Fatigue data from the combined LCF, HCF and dwell fatigue tests are presented in Fig. 3.
Therefore, the current data suggests that Alloy 104 is insensitive to dwell, similar to Ti-6Al-4V, where any reduction in fatigue lives under dwell compared to cyclic waveforms only occurs at extremely high levels of applied stress, approaching 95% of the static strength and above.
Fig. 3: S-N data for Alloy 104 in two heat treated variants. (* Ti 6/4 data from reference [12]).
[11] Davies, P., unpublished data, Swansea University, 2013
[12] Bache, M.R., private data

Data driven techniques have been applied in many chemical processes.
This paper is used PCA and FDA to produce a lower-dimensionality, PCA is a dimensionality reduction technique which transforms correlated original multivariate data to a set of uncorrelated data [14].
Sampling time was used to collect the simulated data for the training and testing data is 3 minutes.
Let the original data set, where each row is a single sample of data set and each column is an observation.
Reduction order A reduced set of a smaller number ‘a’ (adata are good for fault detecting.

PCA is a classical feature extraction and data representation technique widely used in the areas of pattern recognition and computer vision[2].
However, PCA only uses the second order statistical information in data and fails to perform well in nonlinear cases.
LDA is a traditional statistical technique for dimensionality reduction[4].
On nonlinear dimensionality reduction for face recognition.
On nonlinear dimensionality reduction for face recognition.

Based on comparable price energy input-output table of Xinjiang to research low carbon economic development strategy Yuansheng Huang 1, a, Lutong Li 2,b 1 College of Business Administration, North China Electric Power University, Baoding, 071000, China 2 College of Business Administration, North China Electric Power University, Baoding, 071000, China ahys2656@yahoo.com.cn, blilutong302@qq.com Keywords: input-output; implicit carbon; energy saving and emissions reduction Abstract.
Data Sources.
The energy input-output table takes the input-output table of 1992,1997,2002 and 2007 drew up by the National Bureau of Statistics as the foundation, and the data of the “National Accounts”“Energy Production and Consumption”and other parts come from“China Statistical Yearbook”.The data of the energy imports and exports, the energy balance sheet, the energy consumption of the terminal industrial departments and so on are quoted out of the “China Energy Statistical Yearbook”.
Meanwhile, the data of the depreciation rate of fixed assets of various departments, the new fixed assets and the delivery utilization rate of the fixed assets and others delivery rate are from the “Statistical Yearbook of Investment in Fixed Assets”.
Carbon dioxide emissions s and economic growth: Panel data evidence from developing countries [J].

Data processing examples show that the model's practicality and reliability.
System behavior data could be desultorily, intricate, but between them there are always certain regularity .
Accumulated generating operation and inverse accumulated generating operation is Reciprocal operation , that’s to say ,accumulated once sequence can be through inverse accumulated generating operation by generation reduction for the original data sequence .
If the data changes slowly, the two model have unanimous results with a little dissimilarity .
Data processing examples show that the model's practicality and reliability .

Table 2 presents details of testing conditions and particle size distribution data obtained by laser diffraction such as d10, d20, d30, d50, d80, d90, the surface mean diameter D[3,2] and the volume mean diameter D[4,3].
Summary data of physical properties of raw powders and sands.
Its main mineralogical, chemical and physical features are summarized in Table 3 (data made available by the producer company) [15].
These results are very interesting since the blended mortars presented a significant reduction in the Portland cement consumption (up to 35%, by mass) and, consequently, a reduction in the greenhouse gas emissions.
To study the influence of ratio, k-factor, activity index and strength gain of raw powder on mechanical properties, data analysis was conducted using software SPSS.

The utility of fossil fuel depleted its existence, degraded the environment and led to reduction in underground carbon resources.
The worldwide reduction of underground carbon resources can be substituted by the bio-fuels.
Experiments were initially carried out on the engine using diesel as fuel in order to provide base line data.
After engine conditions stabilized and reached to steady state, the base line data were taken.
The presence of camphor oil in the blend enhances the combustion process, which is reflected in the reduction of CO emissions.

The model has made an accurate check by the existing accident data.
As referred above, any function relation can convert to the fractal distribution form using the concept of variable dimension fractal, however, the data obtained from the actual are often just some of discrete data points in the forecast of mine accident.
So it is difficult to get certain function relations from these data points, at this time, the data can be made a series of transformations, ensure that the converted data fit well the fractal distribution model and are more suitable for mine accident forecast[6], specific algorithm process is as follows: Step1: Calculate every two points between the fractal dimension of the original accident data (Ni,ri)(i=1,2,…,n), get fractal dimension D of n-1 periods, if these values of are close to each other, small discrete degree, then turned to Step4, otherwise turned to Step2.
(2)Process origin data by the first-order data accumulation, the second-order data accumulation , the third-order data accumulation according to the Eq.(7), Eq. (8), Eq. (9), get sequence {S1j}, {S2j}, {S3j}, then calculate the fractal dimension between every two points of the three series respectively, which is noted as D1, D2 and D3 , and each sequence can get 12 fractal dimension.
(13) r = 14, r = 15 is taken into Eq. (13) ,and get the 14th and 15th value of S3: S314=42772 S315=51394 Using the above values to calculate by inverse accumulative reduction method according to the E.q (11), E.q (12), and get prediction values of 14th and 15th data: N14=73,N15=45 The 14th and 15th practical accidents numbers are 75 and 42 calculated by known data, the prediction data and the actual data are comparative analyzed, get the average relative error is 4.8%.So we can get the conclusion that the error between prediction data and the actual data is small, which indicates the application of forecasting model based on fractal theory to the mine accidents prediction is reasonable and practical.