Artificial Neural Network Modeling Economics Essay
Abstraction: In this paper Artificial Neural Network ( ANN ) theoretical accounts are employed to calculate the unit land monetary value of Sowcarpet, which is located in the nucleus metropolis every bit good as a portion of Central Business District ( CBD ) of Chennai. The monthly mean value of the selected factors such as National Gross Domestic Product, cost of rough oil, dollar equality to Indian currency, rate of rising prices, gold and silver monetary value, Mumbai and National portion index, population in the survey country, involvement rate on place loan, unit cost of building, guideline value and clip factor from the twelvemonth 1997 to 2008 are considered in the survey and the theoretical accounts are validated with the land monetary value of 2009 and 2010. The theoretical accounts are used to calculate the land monetary value for the following five old ages and found that there will be a unvarying one-year addition of 17 % in the selected location.
Keywords: Land Price, economic factors, nervous web, land monetary value theoretical account, future tendency.
Over the last two decennaries at that place have been a batch of research surveies analyzing land monetary values. Each survey includes properties of land monetary value such as geographical location, the environment, size of secret plan, land usage form, dirt productiveness, topography, drainage, population growing, economic development, substructure, agribusiness, nearby developments, etc. [ 1 ] – [ 3 ] . Statistical theoretical accounts have been normally used to gauge land monetary values [ 4 ] – [ 7 ] .Recently, unreal nervous web theoretical accounts have been applied in existent estate anticipation [ 8 ] – [ 11 ] . The surveies show sensible truth for complex jobs utilizing ANN theoretical accounts.
From the literature reappraisal, the undermentioned important factors that influence the land monetary value tendency are selected for the survey: Gross Domestic Product ( % ) , Cost of petroleum oil ( $ ) , Dollar equality to Indian currency ( Rs ) , Rate of rising prices ( % ) , Gold and Silver monetary value per gm ( Rs ) , Mumbai and National portion index, Population in the survey country, Interest rate on place loan ( % ) , Unit cost of building per Square pes, Guideline value per land ( Rs ) and Time factor ( Year and Month ) . This survey focuses on unreal nervous web to measure the influence of economic factors on land monetary value and its future tendency.
Land is an immoveable, scarce resource, which helps to carry through the basic demand of a human. Owning a land and house is a esteemed issue in the society and because of possible it becomes an investing option now. Effective use of land becomes an built-in portion of urban development. The urban-based economic activities account for more than 50 % of Gross Domestic Product ( GDP ) in all the states. In India by 2011, urban country will lend 65 % to GDP. The agricultural land was 84 % in the twelvemonth 1980 and it will shrivel to 35 % in 2020 due to rapid urbanisation. Major urbanisation force per unit area is to be addressed due to mass migration of people from little towns to urban centres. Soon 41 metropoliss in India have more than one million population but before two decennaries, it was merely 33 metropoliss. In 2050, India needs to suit 900 million more people in metropoliss, which requires 18500 square kilometres of land as per the conventional planning norms. Harmonizing to World Development Indicator study, India ‘s urban population will increase to 75 % in 2050 from 38 % in 2009. Due to limited handiness of land and to use it optimally, the development tendency easy shifted in perpendicular way instead than radial and horizontal. This compact perpendicular development will do positive environmental impact and leads better handiness and efficient conveyance.
Economic base of Chennai metropolis has shifted from trade and commercialism to disposal and services. Buoyant Economy, increased employment rate, high disposable income, cosmopolite ambiance and improved life manner are instrumental in driving the demand for high-rise flats. The demand on residential belongings is consistent, monetary value are besides mounting up due to boost in the input cost. There is immense demand on developed secret plans and the supply degree is virtually shrunk leads to boost in land monetary value. In a market dominated by the terminal users, demand to provide mismatch continues. Invest on land for a unafraid hereafter becomes a world in India. Investment made on land outputs better returns than flats and other traditional investing options, at the scope of 100 to 300 % over past few old ages in South and West suburbs of Chennai. Generally, the land monetary value depends on economical, societal and physical characteristics. Compared to old old ages the market has stabilized. Undertakings along the Old Mahabaliburam Road ( OMR ) have seen most new gross revenues. The market is seeing a positive impulse with occupation security which increased figure of terminal users. Most lodging finance companies have kept their place loan rates stable without much addition helps to stabilise the market. Reasonable involvement rate, increased supply and low-cost monetary values are some grounds to foretell the market will go on to make good. The resurgence of Information Technology ( IT ) sector taking to creative activity of new occupations and increased liquidness is besides expected to give the land and lodging market in Chennai a positive impulse. The survey on land monetary value tendency becomes of import to hold a better thought on future land monetary value which helps in be aftering issues.
About Chennai Metropolitan Area ( CMA ) and the Study Area
Vision 2026 is to do Chennai as a premier Metropolis, which will be liveable, economically vivacious and environmentally sustainable. Chennai is the fourth largest metropolitan metropolis in India. The City is at the nucleus of CMA and is the Centre for all commercial and societal activities every bit good as a life country for bulk of population. It is the topographic point of focal point on economic and cultural development. Chennai is situated on the Coromandel Coast in South India and the land is plane, which is located with latitude between 12050’49 ” and 13017’24 ” and longitude between 79059’53 ” and 80020’12 ” . CMA comprises Chennai City Corporation, 16 municipalities, 20 town panchayets, 204 small towns organizing portion of 10 panchayat brotherhoods in Thiruvallur and Kancheepuram territories. It extends over 1189 square kilometer country.
Chennai metropolis and CMA have 55 and 70 hundred thousand of population severally in 2009. It has a steadfast base of big industries and commercialism including insurance, transportation and banking. The metropolis has dramatically changed over a period and mushrooming of commercial edifice is an out-come of the altering spacial kineticss. From 1994 to 2007, Chennai metropolis ‘s GDP grew at 6.5 % while the provinces GDP grew at 6 % . The part of CMA to province GDP is 40 % . Chennai histories for 30 % of national car industry, 15 % of package exports and 50 % of leather exports. Land monetary value scouring in metropolis country and the development along IT corridor in South and electronic hardware corridor on West has given a practical encouragement to land proprietors to increase the monetary value. The extortionate land value, which in bend upped the flat monetary values to a new high in the metropolis countries and in suburban belongingss, has a push on substructure development.
In existent estate slack, the suburbs foremost bear the burnt, followed by City country and eventually the CBD. Similarly, during an upturn, belongings resurgence first happens in muffussal country and the CBDs are the last to better. Second maestro program released by Chennai Metropolitan Development Authority ( CMDA ) [ 12 ] envisages a series of matter-of-fact step for optimal use of available land. Higher FSI at 2.0 and redefining particular edifices will travel the tardy developments. A study by ICICI belongings services reveals that 30.70 million sq.ft. of residential infinite affecting more than 21000 units by class A, B and C developers will come in in to the market by the terminal of 2009. Tidel park, bing industrial estates in Guindy and Ambattur, upcoming Sipcots on the peripheries and IT units in West and Southern parts, proposed international airdrome, rapid conveyance and tube trains, over Bridgess, elevated and round ring roads are the extra power of Chennai real property sector and the land monetary value rise.
3.2 Study Area
Sowcarpet is one of the of import parts of George Town ( GT ) , which is the CBD of Chennai metropolis. This country is abounding with jewellery stores, electrical stores, hardware stores, conveyance engagement offices, vegetable and fruit markets, etc. The assorted land usage form, narrow and weaving unplanned route web which carries immense volume of assorted traffic more than its capacity have resulted a gradual debasement in the environmental quality of the country. It is filled with relocated population from North India, making commercial, retail and sweeping concern. Sowcarpet has 0.62 square kilometer country with latitude of 13005’29.15 ” N and longitude 80016’52.39 ” Tocopherol and an lift of 13 metre above average sea degree and its location in Chennai metropolis is shown in Figure 1.
Figure1.Location of Sowcarpet
The route web of Chennai is dominated by a radial form meeting at GT. Arterial roads taking to CBD transporting heavy traffic due to concentration of commercial, industrial and immense volume of employment related activities in the CBD are extremely congested. Capacity of all the roads in CBD is reduced due to hapless quality of siting surface and unequal pathway installations and unplanned intersections. Sowcarpet has 52 roads with entire length of 14.6 kiolmeter and route to country ratio of merely 0.14 which really much lesser than the urban planning guidelines. Even though the range of broadening of bing roads is negligible, many roads are converted into commercial zones. GT and Harbour becomes the commercial Centre of the metropolis. GT and its extension in South into Annasalai had the sweeping trade, specialized retail trade and banking and fiscal establishments and commercial activity was intense. More than two lakhs occupations representing 48 % of the entire work topographic points in the CMA in 1971 were located here. General Hospital and Government Stanly Medical Hospital serves the CMA, is located following to sowcarpet. The growing rate of population in Chennai metropolis and GT was in falling tendency in the past two decennary from 28 to 16 % and from 12 to 7.4 % severally. The growing of country and population is shown in Table 1.
Table 1. Population and its Growth in
Chennai City ( CC ) and George Town ( GT )
Area ( Sq. Km )
Population ( Lakhs )
Due to the influence of economic lag the one-year figure of land minutess registered in the enrollment office of Sowcarpet starts declined upto 80 % compared to the twelvemonth 2007 after a sustained growing of past two decennaries. The consequences of questionnaire study from the respondents of Sowcarpet outputs the undermentioned information that it is located really near to Central railroad station. Location of school, multi forte infirmary, vegetable markets and major coach end point nearby High tribunal are accessible from merely 0.5 to 2 kilometre. Urban services like H2O supply, sewer drain, stome H2O drain and cleansing of refuse are satisfactory but the degree of noise pollution is well high. Immigrated colonies from North India and from Andhra Pradesh, plentifulness of concern and commercial activities like jewelry, cloth garments, hardware and electrical stores, are felt as the major factors of monetary value rise of land and rental value of abode in Sowcarpet. Soon a two sleeping room level rents in five-digits and many house proprietors want to rent the house for immense amount of money.
The existent estate growing in the metropolis was dominated by the CBD and environing locations like Annasalai until 1990s. However, the scarce land handiness and high existent estate costs forced companies with big infinite demands away from CBD. The current growing form of the metropolis focused on the countries where authorities is be aftering roads and other substructure betterments. Decentralization of activities like vegetable market, flower bazar and muffussal coach stand to peripheral countries like Koyambedu, Sathangadu and Madhavaram which are extremely decongested the GT, will better the life quality. Land monetary value of CBD rise twelvemonth by twelvemonth. This is much above the affordability of the lower and middle in come group population. Triplicane, Mylapore, Purasiwalkam and the Northern portion of GT like Royapuram are the old residential characterized by row lodging with shopping along chief roads. Shoping installations of local significance had developed along about all major roads. Experts say that for long term investors CBD country offer range as even among commercial and residential sector one takes a whipping, other sector will come to deliver so that there will be consistence in the flow of return on investing. The land monetary value patterning survey helps to determine the alterations in growing occurred in the yesteryear and the grounds for the same. It will assist to place the potency for future growing and in planning facets. To quantify the rise of land monetary value over a period of clip is indispensable for future policy implicating and to measure the compensation sum for the land which will be acquired for public intent.
Theory of Artificial Neural Network
ANN is a computational engineering from the unreal intelligence subject whose architecture emulates the web of nervus cells in the human encephalon. An NN is a parallel distributed information-processing construction dwelling of treating elements ( PEs ) which contains local memory. The PEs can besides transport out localised information processing operations interconnected via unidirectional signal channels called connexions. NN architecture such as a standard Back-propagation ( BP ) NN can be developed by utilizing the assorted indexs as PEs to be investigated upon. The construction of back extension is shown in Figure 2.
Figure 2. Back extension Network
As in biological systems, the strength of these connexions alterations in response to the strength of each input and the usage of transportation map by the PEs. All nodes ( which are indexs ) in the input-layer are to the full connected to each of the concealed nodes in the hidden-layer and the procedure of larning involves all the input nodes and the concealed nodes. In other words, larning besides involves all the other input nodes with each input node connected to every concealed node. The end product value from each node of the concealed bed in bend becomes the excitant input-value for a peculiar node in the end product bed. In this survey, there are 13 indexs, that is PEs, and one prejudice node in the input bed of the NN theoretical account is constructed. All the input values are normalized utilizing the MinMax Table.
The rule behind this standardization procedure is:
Normalized value, N= [ Original value – Minimum value ] / [ Maximum value – Minimum value ]
Where, 0 a‰¤ N a‰¤ 1
The faculty learns the implicit in latent map through an mistake gradient-descent method and the preparation stops when the root-mean-Square-error for Output-target values falls below 0.0001 per centum. It takes 88 Epochs to make the coveted mark. More loop in the preparation of informations improves convergence. Each concealed node ( that is H1 to H3 ) receives a set of feed-in signals ( or values ) from which an end product value is generated. Finally, all nodes in the hidden-layer are to the full connected to the end product node.
Share of Influence Input Node, Ii, asserts on the topic Output Node = S I %
I?njj=1 ( |wij||oj| ) / ( I?ni i=1|wij| )
S I = X 100 ( 1 )
I? ni i=1 I?nj j=1 ( |wij||oj| ) / ( I? ni i=1|wij| )
Where ni = figure of input nodes
nj = figure of concealed nodes
wij = connexion – weight from input node Ii to hidden-node Hj
oj = connexion – weight from concealed node Hj to subject end product node Si
An ANN learns to work out specific jobs without the demand for job – specific algorithms. The acquisition scheme incorporates the minimisation of average square mistake across all preparation forms. The user can put a desirable consequence and compare the web ‘s public presentation with the mark preparation set.
In the development of executable nervous web solution all 13 indexs are used to determine the consequence and to foretell the tendency of land monetary value, thereby to continue dependability in subsequent comparing on the truth of nervous web solution. BP NN is chosen as a basic since, it is widely accepted. The purpose of the acquisition procedure is to minimise the planetary mistake E of the system by modifying the weights. A gradient descent regulation is adopted in the acquisition across the preparation set. Suppose a vector I is presented as the input bed of the web and the coveted end product is D. Let O denote the existent end product produced by the web with its current set of weights. Then the step of the mistake in accomplishing that desired end product is given by:
kE = 0.5 I? ( Dk – Sooner state ) 2 ( 2 )
ANN is set to 10000 loops. Training Michigans when convergence obtains at the needed root-mean-square-error or when the mistake across the acquisition axiom generated by web has become systematically stable. Prognosiss are being made over a period between 2011- 2015 and the Run duologue box in the nervous programme will assist to set up the existent end product. The portion of influence of selected indexs is established utilizing Garson ‘s method. In this respect, the nervous programme has the NN tool duologue box that shows the alteration in end product by weightages. This helps to cognize which of the indexs has the most consequence on the end product.
Consequences and Discussion
The prognosis ability of the nervous web solution is shown in Table 2. The existent and ANN theoretical account monetary values are compared and it can be seen that the difference is approximately 3 to 4 % . This indicates that the identified indexs may be used as dependable inputs for mold of land monetary value and besides the theoretical account is validated with the monetary values in the old ages 2009 and 2010.
Table 2. Prediction ability of ANN theoretical account
Actual Market Price ( Lakhs )
Model Price ( Lakhs )
Table 3 shows the portion of influence of identified factors towards the end product node. ANN solution has ranked Construction Cost, Dollar equality and Crude oil monetary value as major act uponing factors towards Land monetary value.
Table3. Explanatory strength of indexs in ANN theoretical account
I? j=1 [ ( |wij||oj| ) /
( I? i=1|wij| ) ]
Share of Influence
Strength of Indexs
Crude oil monetary value
Home loan involvement
Silver monetary value
Gold monetary value
Sum of signal transportation
The validated land monetary value theoretical account and the hereafter theoretical account are shown in Figures 3 and 4, severally. From the consequences, the anticipations offered an mean STDEV of 3.75 which is fringy and the one-year rise of land monetary value in Sowcarpet will be 17 % .
Figure 3. Validated Land Price Model
Figure 4. Forecasted Land Price Model
In this paper, the land monetary value at Sowcarpet in Chennai City is evaluated by Artificial Neural Network. Artificial nervous web theoretical account monetary values are tested for their prognostic power utilizing economic factors collected from the twelvemonth 1997 to 2008. The forecasted consequences show that the one-year rise in land monetary value at Sowcarpet is approximately 17 % in the following 5 old ages.