Application of ANN Model

Application of ANN Model 4.0. Introduction In this chapter, the results of ANN modelling are discussed through performance parameters, time series plotting and presentation through tables. Before the application of ANN model, statistical analysis of data are done. It is discussed earlier that the selection of appropriate input combination from the available data is the crucial step of the model development process. Five different types of input variable selection (IVS) techniques were utilized and twenty six input combinations were prepared based on the IVS techniques which are discussed in section 4.2. Finally, results of four ANN models are discussed one by one. Firstly, the feed forward neural network model were picked to predict dissolved oxygen of Surma River with all twenty six input combinations and compared with one another. Secondly, the sensitivity analysis was done by changing the value of individual input variables in a certain percentage. Thirdly, six best input combinations were selected based on their performan ces and rest of the three ANN models were utilized with those selected six input combinations. Finally, three best models from each ANN model were picked to compare with each other. The results of statistical data analysis, results of IVS, and results of ANN models will be discussed in this chapter chronologically. 4.1. Statistical Analysis of Data: Statistical parameters are very important components to understand the variability of a data set which is prerequisite of any modeling works.This study used some basic statistical parameters i.e. minimum, maximum, mean, standard deviation (SD) and coefficient of variability (CV) as defined below: Where, N is the total number of samples, is the water quality data, is the arithmetic mean of that particular data series. The summary of analysis is represented in Table 4.1. Standard Deviation (SD) shows the variation in data set, where smaller value represents the data is close together, while larger value denotes wide spreading of data set. The SD of dependent variable (BOD) showed relatively small value with respect to other parameters. But sometimes its difficult to understand variability only by SD value. Thus, coefficient of variability (CV) was used in this study for clear understanding of variability. Value of CV for BOD displayed larger variation (75%) that represents huge quantities of untreated wastewater was dumping from various point and nonpoint sources into this river during sample collection. All independent variables (remaining 14 parameters) also showed an enormous variation in CV value (8% to 144%). Such variability might be happened due to geographical variation s in climate and seasonal inà ¯Ã‚ ¬Ã¢â‚¬Å¡uences in the study region. pH showed lowest variation and it may happen due to the buffering capacity of the river. Table 4. 1: Basic Statistics i.e. minimum (min), maximum (max), mean (M), standard deviation (SD) and coefficient of variation (CV) of the measured water quality variables for a period of three years (January, 2010-December, 2012) in Surma River, Sylhet, Bangladesh. Variable Min Max Mean Std. CV (%) Phosphate (mg/l) 0.01 3.79 0.53 0.70 132 Nitrates (mg/l) 0.18 4.0 1.53 1.05 69 CO2 (mg/l) 8.0 127 32.66 20.99 64 Alkalinity (mg/l) 21 195 59.34 30.56 51 TS (mg/l) 55 947 292.2 165.69 57 TDS (mg/l) 10 522 142.3 102.15 72 pH 5.7 8.25 6.92 0.55 8 Hardness (mg/l) 45 262 119 43 36 SO4-3 (mg/l) 2.0 33.10 10.68 6.82 64 BOD (mg/l) 0.6 17.3 3.79 2.86 75 Turbidity (NTU) 4.18 42.62 11.84 7.37 62 K (mg/l) 1.47 35.22 5.45 5.75 106 Zinc (mg/l) 0.1 0.52 0.19 0.09 47 Iron (mg/l) 0.09 6.09 0.48 0.69 144 DO (mg/l) 1.9 17.30 5.40 2.45 45 4.2 Results of input variable selection: It is mentioned earlier that selection of appropriate input variables is one of the most crucial steps in the development of artificial neural network models. The selection of high number of input variables may contain some irrelevant, redundant, and noisy variables might be included in the data set (Noori et al., 2010). However, there could be some meaningful variables which may provide significant information. Therefore, reduction of input variables or selection of appropriate input variables is needed. There are so many IVS techniques available such as genetic algorithm, Akaike information criteria, partial mutual information, Gamma test (GT), factor analysis, principal component analysis, forward selection, backward selection, single variable regression, variance inflation factor, Pearsons correlation and so on. In this research, five IVS techniques such as factor analysis, variance inflation factors, and single variable -ANN, single variable regression, and Pearsons correlation (PC) are utilized to find out appropriate input combinations. The explanation of five selected IVS techniques are explained with the respective input combinations. 4.2.1. Factor Analysis: Factor analysis is a method used to interpret the variance of a large dataset of inter correlated variables with a smaller set of independent variables. At the initial stage, the feasibility study was carried out for the input variables used in this study was done by KMO index and correlation parameter matrix. The data are suitable for factor analysis if KMO index is greater than 0.5 and correlation coefficient is higher than 0.3. According to Table 4.1, the data are feasible for factor analysis as the KMO index of all data is found as 0.720 (greater than 0.5) and a null hypothesis (p=0.000) indicates a significant correlation between the variables. Moreover, from Table 4.2, many of the correlation coefficient (Pearsons) between water quality parameters are greater than 0.3 which also confirms the feasibility of water quality parameters for factor analysis. Table 4.3 describes the eigenvalues for the factor analysis with percent variance and cumulative variance. To find out the numbe r of effective factor, factors with Eigen values 1.5 are considered for ANN model. The scree plot of Eigenvalues are illustrated in Figure 4.2. As observed in Figure 4.1, the Eigen values are in descending order and a drop after 2nd factor confirms the existence of at least two main factors. Table 4.2 Coefficient of KMO and Bartlett test results Kaiser-Meyer-Olkin Measure of Sampling Adequacy 0.720 Bartletts Test of Sphericity Approx. Chi-Square 533.3 Df. 78.00 Sig. 0.000 Normally, factors having steeper slope are good for analysis whereas factors with low slope have less impact on the analysis. The first two factors cover 64.607% of total variance (Table 4.4). The results of rotated factor loading using Varimax method are tabulated in Table 4.5. The results indicated that the first factor is CO2, Alkalinity and K+, which are the most influential water quality parameter for Surma River. However, hardness, total solid (TS), Fe and total dissolved solid (TDS) are grouped in the second factor. Figure 4.1 Scree plot of eigenvalues of the Surma River Table 4.4 Individual eigenvalues and the cumulative variance of water quality observations in the Surma River Factors Eigen Values % Variance Cumulative Variance % 1 3.800 29.227 29.227 2 1.839 14.147 43.374 3 1.553 11.947 55.321 4 1.207 9.286 64.607 5 0.997 7.668 72.275 6 0.802 6.172 78.447 7 0.645 4.965 83.412 8 0.639 4.914 88.326 9 0.442 3.400 91.727 10 0.331 2.548 94.275 11 0.304 2.341 96.615 Table 4.5 Rotated factors loading for water quality observations in the Surma River using a Vartimax method 12 0.241 1.855 98.470 13 0.199 1.530 100.000 Factor NO3 pH CO2 Alk. Hard. TS BOD Tur. K+ Fe TDS PO4-3 01 .070 .173 .791 .876 .238 .273 -.178 .443 .859 -.038 .079 .179 02 .133 -.22 -.004 .143 .702 .797 .007 .141 .176 .621 .787 .165 03 .789 -.41 -.050 -.13 .107 -.25 .152 -.526 -.010 .114 -.135 .613 04 .156 .737 -.199 -.057 -.283 .117 .613 .287 -.079 .416 -.162 .170 Phosphate and nitrate are grouped in factor 3 whereas pH, BOD, Fe are grouped in factor 4. In this research, the variables in the first, second, third and fourth factor are named as the M16, M17, M18 and M19 respectively. All the model names along with their respective variables are tabulated in Table 4.6. Table 4.6 results of factor analysis with their respective inputs Model Input Variables FA I CO2+ Alkalinity + K+ FA II Hardness + TS + Fe + TDS FA III NO3+ PO4 -3 FA IV pH +   BOD 4.2.2. Variance Inflation Factor The variance inflation factor (VIF) is a method which measure the multi-collinearity in a regression analysis. In this study, variance inflation factors (VIF) were utilized to find appropriate inputs for the proposed model. The performances of VIF are tabulated in Table 4.7. It is found that, the VIF value is not that much satisfactory for all the variables. However, alkalinity, potassium, total solids and phosphate show quite a good result. To prepare some effective input combination for the ANN model, alkalinity was preferred for the model first and all the variables were added one by one. Moreover, only alkalinity is individually not considered in the model as the SV-ANN shows a weak performance for alkalinity (Table 22222).   Eleven input combinations were prepared based on the VIF value which is shown in Table 4.8. Table 4.7 Result of variance inflation factor for individual variables Input Combination VIF Alkalinity (mg/l) 3.180 K+ (mg/l) 2.847 TS (mg/l) 2.628 PO43- (mg/l) 2.070 CO2 (mg/l) 2.036 TDS (mg/l) 1.997 pH 1.898 Hardness (mg/l) 1.820 Turbidity (NTU) 1.696 Fe (mg/l) 1.290 BOD (mg/l) 1.177 NO3 (mg/l) 1.175 Table 4.8 Results of variance inflation factor (VIF) with their respective inputs Model Input Combinations VIF-I Alkalinity + K+ VIF-II Alkalinity + K+ TS VIF-III Alkalinity + K+ TS+ PO4-3 VIF-IV Alkalinity + K+ TS+ PO4-3+ CO2 VIF-V Alkalinity + K+ TS+ PO4-3+ CO2+TDS VIF-VI Alkalinity + K+ TS+ PO4-3+ CO2+TDS+ pH VIF-VII Alkalinity + K+ TS+ PO4-3+ CO2+TDS+ pH+ Hard VIF-VIII Alkalinity + K+ TS+ PO4-3+ CO2+TDS+ pH+ Hard+ Tur. VIF-IX Alkalinity + K+ TS+ PO4-3+ CO2+TDS+ pH+ Hard + Tur. + Fe VIF-X Alkalinity + K+ TS+ PO4-3+ CO2 +TDS+ pH+ Hard + Tur. + Fe + BOD VIF-XI Alkalinity +K+TS+PO4-3+CO2+TDS+pH+Hard+Tur. +Fe + BOD + NO3 4.2.3. Pearsons correlation coefficient   It is not always true that all the variables should contribute to simulate the value of other parameters. Some variables can have a very good relationship with other, some may have weak connection. Pearson correlation is an effective option to understand the relationship with one variable to another. While modelling DO value for the Surma River, it is important to select the variables to have positive relationship with one another. For this reason, a Pearson correlation was prepared which is tabulated in Table 4.3. It is found that there are 4 different types of data combinations which have positive and significant relationship with each other as tabulated in Table 4.9. Table 4.9 Input combinations using Pearson correlation Model Input Combinations PC I Alkalinity + TDS+ PO4-3+CO2+K+ PC II pH + Hardness + Turbidity PC III Alkalinity + Hardness+ TS+CO2+K+ PC IV Hardness+ TS+ K+ Turbidity PC V Hardness+ TS+ Fe +TDS PC VI TS + Turbidity + Fe +TDS + K+ 4.2.4. SV-ANN The performance of single variable artificial neural network was also done to find out appropriate input variables for the proposed model. All the individual variables are separately trained, tested and validated. During utilization of SV-ANN, only correlation coefficient (R) is considered to select the appropriate variables. The performances of SV-ANN are tabulated in Table 4.10 for testing, training and validation array. From the analysis, it is found that the individual variables show a weak performance. Only TS and BOD perform better comparing with other variables.   The SV-ANN with TS shows a correlation coefficient of 0.596, 0.600 and 0.700 for testing, training, and validation phases respectively. Moreover, the respective correlation coefficient (R) for SV-ANN model with BOD are found as 0.578, 0.574 and 0.652 for testing, training and validation. However, turbidity, carbon di oxide, phosphate and nitrate have quite good relations with DO. As individual variables did not pro vide significant result, the variables are not considered in the ANN model individually. BOD and TS have quite well Table 4.10 the correlation coefficient (R) for single variable ANN and single variable MLR Variables Phase SV-ANN SV-MLR R R PO43- (mg/l) Testing 0.439 0.115 Training 0.549 Validation 0.440 NO3 (mg/l) Testing 0.211 0.148 Training 0.311 Validation 0.112 pH Testing 0.234 0.087 Training 0.201 Validation 0.432 CO2 (mg/l) Testing 0.391 0.057 Training 0.453 Validation 0.514 Alkalinity (mg/l) Testing 0.222 0.200 Training 0.211 Validation 0.099 Hardness (mg/l) Testing 0.139 0.089 Training 0.649 Validation 0.155 TS (mg/l) Testing 0.596 0.199 Training 0.600 Validation 0.700 BOD (mg/l) Testing 0.578 0.100 Training 0.574 Validation 0.652 Turbidity (NTU) Testing 0.431 0.183 Training 0.583 Validation 0.398 K+ (mg/l) Testing 0.111 0.046 Training 0.543 Validation 0.219 Fe (mg/l) Testing 0.217 0.002 Training 0.210 Validation 0.306 TDS (mg/l) Testing 0.222 0.084 Training 0.345 Validation 0.245 relations with DO so they are grouped in one model (SV-ANN I) and turbidity, carbon di oxide, phosphate and nitrate are grouped in another one (SV-ANN II). The input variables utilizing SV-ANN is tabulated in Table 4.11. 4.3.5. SV-MLR Like the performances of single variable ANN model, SV-MLR with all the input individual variables show weak performance. Moreover, variables like alkalinity, nitrates, total solid and turbidity show good result comparatively. The performances of SV-MLR are tabulated in Table 4.10. It is found that, alkalinity and TS show quite good results comparing with other variables and hence they are grouped together (SV-MLR I). Another model (SV-MLR II) was prepared using all the variables with correlation coefficient more than 0.200. The input variables using SV-MLR model are tabulated in table 4.12. Table 4.11 results of single variable artificial neural network with their respective inputs Model Input Variables SV-ANN-I TS + BOD SV-ANN-II TS + BOD+ PO4-3+ CO2+Turbidity Table 4.12 results of single variable multiple linear regression with their respective inputs Model Input Variables SV- MLR I Alkalinity + TS SV-MLR II Alkalinity + TS + Turbidity + NO3 Model IVS Type Input Variables M1 PC I Alkalinity + TDS+ PO4-3+ CO2 +K+ M2 P

Economics: The Functions of Money

1. What are the functions of money? (5) Money is anything that is generally accepted as payment for goods and services and repayment of debts. The main functions of money are distinguished as: a medium of exchange, a unit of account, a store of value, and occasionally, a standard of deferred payment. Money's most important function is as a medium of exchange to facilitate transactions. Without money, all transactions would have to be conducted by barter, which involves direct exchange of one good or service for another. The difficulty with a barter system is that in order to obtain a particular good or service from a supplier, one has to possess a good or service of equal value, which the supplier also desires. In other words, in a barter system, exchange can take place only if there is a double coincidence of wants between two transacting parties. Store of value. In order to be a medium of exchange, money must hold its value over time; that is, it must be a store of value. If money could not be stored for some period of time and still remain valuable in exchange, it would not solve the double coincidence of wants problem and therefore would not be adopted as a medium of exchange. 2. Explain why gold no longer performs the functions of money in the British economy? (5) The point of the gold-exchange standard is that it cannot last; the piper must eventually be paid, but only in a disastrous reaction to the lengthy inflationary boom. As sterling balances piled up in France, the U. S. , and elsewhere, the slightest loss of confidence in the increasingly shaky and jerry-built inflationary structure was bound to lead to general collapse. Thus the failure of inflated banks throughout Europe, and the attempt of hard money. France to cash in its sterling balances for gold, led Britain to go off the gold standard completely. Britain was soon followed by the other countries of Europe. The gold exchange standard was one of the elite collectivist bankers crowning accomplishments. But more coups were yet to come. In 1933 the bankers convinced Roosevelt to call in all private holdings of gold – essentially taking the money of the people. Gold was outlawed. Paper money was no longer redeemable in gold. This is why gold is not considered money in Britain. 3. Why are credit cards not money? (4) Money, in any form, is generally recognized as a very liquid asset, that is an asset that can be quickly converted to cash or used as cash Credit cards work in the same manner as a loan. If you buy an item using a credit card, the credit card company will pay the shopkeeper today and you will have an obligation to pay the credit card company when your credit card bill comes in. This obligation to the credit card company does not represent money. The money part of the transaction between you and the credit card company only comes into play when you pay your bill. So credit cards are not considered to be money. 4. Why is money in the current account of banks considered as money? (4) We have different types of accounts; savings accounts, current accounts and so on. But in this case, the bank rather takes the money you are supposed to receive as interest from you. That interest becomes a source of income to the bank. 5. What would you expect to happen to the rate of interest if money supply increases? Why? Draw a Diagram. (12) If money supply increases, the rate of interest will decrease. This is because the more money is available, the more loans are available. Competition for borrowers reduces the real interest rate. The NOMINAL interest rate may increase if the increase in the real money supply causes inflation. But in the short run, the interest rate falls, but as prices rise the interest rate will rise up again

Using Apa Research Paper Sample Pdf

Using Apa Research Paper Sample Pdf The Importance of Apa Research Paper Sample Pdf It is an impossible task to compose a persuasive research paper without having and crystal clear outline. Employing an outline template can assist the student organize the paper and eliminate the ideas that aren't pertinent to the intention of the essay. You could also see totally free outline. You could also see presentation outline. The term file is simple to handle and work. APA format is a favorite among students owing to its simple guidelines and approach. The MLA format stipulates the vital guidelines for effectively writing an essay in line with the MLA standards. The APA format given by is in template can help you design your work in accordance with the APA guidelines. All About Apa Research Paper Sample Pdf You do library and Internet research so you can earn a prediction of what's going to occur in your experiment, and after that whether that prediction is right or wrong, you'll have the knowledge to comprehend what resulted in the behavior you observed. There are various points to take into account in order to reach a great research paper by means of either a grid paper template or a lined paper template, based on your preference or the research requirement. Then establish who will become your target audience and produce the content of the paper related to them. Always prepare a plan of action to get started with so that you don't get confused or shed track. You would surely find ample information regarding the world wide web but the credibility of the info isn't guaranteed and thus you would require some expert help which can help you proceed in the proper direction. For example if you're writing a business letter you may use a template that has space assigned for your address, your clients address and similar requisites. To earn a business plan template, you have to modify the typical template that's appropriate for your industry and company. There's a generic template that's readily available for all kinds of businesses. Research proposals are extremely often underestimated. Sampling Method The research sampling method which will be used inside this study is random sampling to get a more scientific result that could be utilized to symbolize the entirety of the people. There are lots of good references to aid you with research methodology and technical writing. Some methods and techniques are somewhat more reliable since they h ave been used many times. Completing an MLA outline will make sure your research paper format is accurate. A title page is normally in the middle of the page and is a concise overview of the topic. It's possible to also take a look at this page's Sample Research Papers in addition to these Sample Notebook Papers, which you might also find interesting and helpful. Apa Research Paper Sample Pdf Can Be Fun for Everyone Even when you have some bright suggestions and strong arguments it's still essential to present them in a suitable way. Most theories suggest that only very disturbed individuals do horrible actions if they're ordered to achieve that. After reading the thesis, there ought to be no doubt precisely what the research will be about. Below, you will discover several parts of advice on the best way to take care of your 3-5 page research paper without a lot of trouble. There are a lot of important guidelines to keep in mind while writing. Also, it is going to enhance their organizing skills and allows them to learn more about the subject for making quick arguments. Infant feeding practices refer generally to fulfill the nutritional and immunological needs of the child. There are lots of rules that help you to develop your writing plan. As soon as your order is placed you can be sure of a brilliant bit of work. You will be pleased you filled up the purchase form. For the matter, you may use the New Order option that will make it possible for you to receive in contact with the writers who show interest in your paper, and superior comprehension of your instructions and requirements.

My Long Term and Short Term Goals - 1412 Words

Professional and Personal Goals December 12, 2011 Someone famous once wrote, â€Å"A journey of a thousand miles begins with a single step.† That’s deep! But, in a way, it’s obvious and should go without saying. However, so many people try to just jump the whole thousand miles at once and seem to forget that careful steps and rest stops must be made along the way to successfully (the main word is successfully ) complete that journey. I’ve had my goals and aspirations for a long time but I’m not sure that I ever started out in the most organized fashion. My professional goals remain the same but I now realize that effective time management is the main way to achieve my goals in a less stressful manner. I understand†¦show more content†¦My original plan was to pursue my Bachelor’s Degree after my sons graduated college, since I support them financially, but when I realized that most of the hospitals require nurses to have a bachelor’s degree, I decided that the sooner I start w orking towards my professional long term goal, the better. It goes without saying that the two most important milestones to achieving this goal will be my sons’ individual graduation days. My personal long term goal is to go back to my country of Haiti and offer my assistance to those who have experienced and still experience the hardships and tragedies which the country has undergone. When I left home and came to the United States, I came with a high school diploma but could speak no English. As a single mother, I raised my four sons, worked, and went to school. With the help of scholarships and financial aid, I obtained an Associate Degree in Nursing. I want to â€Å"pay it forward†, as they say, and give back to my country so that others could receive the same opportunity as I did. This long term personal goal will be greatly influenced by finances. Therefore, one of the milestones to achieving this goal is tied into my professional goals (both long and short term). I will need to acquire one of those more stable positions at one of the area hospitals and I will have to be working there for at least a few years before I would feel comfortable enough to ask f or time to return to my country to assist. This is where a timelineShow MoreRelatedPersonal Goals Paper1281 Words   |  6 PagesPersonal Goals Paper Alice Bennett HCS/301 Undergraduate Nursing Studies March 8, 2011 Cora Barrios Personal Goals Paper A goal is defined as something that you hope to achieve. Setting goals will give you long-term vision and motivation; it will help keep you focused on organizing your time and your resources so that you can make the most of your life. 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