Soft Computing Based Model for Trip Production

Soft Computing Based Model for Trip Production Synopsis  On  A Soft Computing based model for Trip Production and Attraction 1. Area of the Proposed Research work Computer Science Applications 2. Research Topic A Soft Computing based model for Trip Production and Attraction 3. Aim and Objectives of research work The aim and objectives of this research is to develop a soft computing based model for trip production, trip attraction mode-wise traffic pattern in Delhi Urban area keeping in view the development polices of the Delhi Master Plan 2021. The proposed model will greatly help in analytical study of the resulting traffic pattern and its forecasting for future city plans. For modeling and analysis of urban transportation system, Delhi has been selected as the study zone. Data on urban activities and traffic flow was collected from the concerned agencies. Delhi, being the Capital of India, is the main center of socio-economic, political as well as cultural activities of the country. Delhi acts as a major center of trade and commerce. The major share of travel needs of Delhi commuters is road based transport system. 4. Literature Review This section focuses on the review of Literature for the study. It is comprises of the topics, related to general facts about the urban transport system. The early trip generation models, based on aggregate data, predicted total trips between city pairs. The modeling methods generally include regression models, cross-classification analysis, or a combination of both. These methods still have applications due to their mathematical feasibility, data availability, and ease of interpretation (USDOT, 1999). Kiron Chatterjee and Andrew Gordon (2006), focuses on the alternative for the Great Britain future scenarios in the year 2030 and the implications they have for transport provision and travel demand. Kiron Chatterjee and Andrew Gordon (2006) develop a National transport model to predict the national road traffics. In order to take income as a constraint for estimating trip generation there is no mathematical model under this aspect. Also, in the developing countries like India wide income disparity is there which can also plays a leading role in trip generation process. Gravity models are signifying the idea of establishing trip distributions process. In Gravity model, the entries of the Origin-Destination matrix are understood to be a feature of the trip counts and other parameters. The main problem of the gravity model is in the measurement of travel cost. This model has been corroborated numerous times as a basic underlying aggregate association (Levinson and Kumar 1995). For the analysis zones separated by a sizeable distances, the gravity model can work properly. But, the denominator approaches to infinity as the distance between locations decreases. In year 1947, Dantzig created the Linear Programming problem as well as offered the simplex method as its solution of Linear Programming. The simplex method was come in existence in year 1951. A simplex method is an iterative process which works along the boundaries of the problems in feasible region to find a solution of the problem. Also, the simplex method still remains the widely known solution finding technique for solving Linear Programming problems. But, the available option on the bases of Linear Programming was not successful in practice. Estimation of trip distribution is a challenging task for future period. In order to compare the performance of intervening opportunity model, gravity model, intervening opportunity model Wilmot et.al (2006) was conducted a study. With the help of this comparison of observed trips and predicted trips, the study recommended that the traditional urban transportation planning trip distribution models are able to model trip distribution at the cumulative level, and that all models traditional models have achieved similar performance and they similar bottlenecks as well. Anthony Chen et.al (2012) presented a basic planning tool particularly targeted at small (Metropolitan Planning Organization) MPOs was proposed to model the system traffic for the planning applications. This tool made use of PFE (Path Flow Estimator) for both the base year estimation as well as the future year predictions with some accessible field and planning data that can be available in public domains. For this tool no formal validation is done Richter.et.al (2012) presented a model based on the logit model. The model is complex. The logit modal choice association states that the probability of selecting a mode for a trip is depend on the relative values of numerous factors such level-of-service, and travel time etc. The complex part of employing the logit modal choice model is to estimating the parameters that can be assigned for the variables presents in the utility function, so the accuracy of this logit model is not ensured. Daniel et.al 2013, developed a inter-urban trip generation model for AkwaIbom, Nigeria, which is based on the multiple regression analysis model for forecasting future patterns. However, in a trip generation model, based on regression approach is used due to the somewhat cumbersome formulation of a choice model for frequency choice. The composite variable that would represent the service characteristics of destinations is excluded. Here, the trip generation is not based on utility maximization and the interrelationship between the trip frequencies. 5. Methodology of the research work Following figure 5.1 shows the flow of work and the model development for trip generation (trip production and trip attraction) model presented in section 5.1, the model development for trip distribution model discussed in section 5.2 and model development for Mode-choice model discussed in section 5.3. Figure 5.1: Flow of work. 5.1 Model Development for Trip Generation (Trip Production and Trip Attraction) Trip generation Process widely used for forecasting travel demands. Therefore trip generation Process is divided into two parts: Trip attraction Trip Production 5.1.1. Model for Trip Production Trip Production process focuses on the total number of trips produced from the city. For empirical implementation of the Trip production model, Artificial Neural Network System (ANN) is used on the available data. The model was trained using data of the year 2003 2004 and validated on data of the year 2005. Whole process of model implementation including training and validation is accomplished in the following steps. Socio-economic data of all the zones are collected. ANN in MATLAB is used to train the model on the dataset for the year 2003 and 2004. The mode model result is validated using data set for the year 2005. Finally, trip production model is used for forecasting of the Number of passenger’s trips production for the year 2021. 5.1.2. Model for Trip attraction Trip attraction process focuses on the total number of trips attracted by the city. For empirical implementation of the trip attraction model, Artificial Neural Network System (ANN) is used on the available data. The model was trained using data of the year 2003 2004 and validated with data for the year 2005. Whole process of model implementation including training and validation is accomplished in the following steps. Socio-economic data of all the zones are collected. ANN in MATLAB is used to train the model on the dataset for the year 2003 and 2004 and then The mode model result is validated using data set for the year 2005. Finally, trip attraction model is used for forecasting of the Number of passenger’s trips attraction for the year 2021. While validation, it was observed that the result produced by the model is very close to the actual data. The average error estimated during the validation phase is low and minimum error is only 0.8%. 5.2 Model development for Trip distribution Trip distribution Process traveler origins and destinations to developed a â€Å"trip table† that displays the number of trips going from every origin zone to every destination zone. For empirical implementation of the trip distribution model, Genetic Algorithm is used on the available data Whole process of model implementation including training and comparison is accomplished in the following steps. Socio-economic data of all the zones are collected. Genetic Algorithm model in MATLAB is used to implement this model on the data set to compute trip distribution for all the zones in DUA. Finally, Comparisons with of results of Linear Programming model done Finally, comparison of Genetic Algorithm based trip distribution model with traditional linear programming is made. The result achieved from traditional Linear Programming Based Model is not up to the mark as the number of input variables increases linear programming based model gives infeasible solution. 5.3 Model development for Mode-choice model Mode choice Process Trip distributions zonal interchange analysis yields a set of origin destination tables followed by; mode choice analysis allows the modeler to determine which mode of transport will be used. For empirical implementation of the mode-choice model, Adaptive Neural Fuzzy Inference System (ANFIS) is used with surveyed data. The model was trained using survey data for the month February 2013 and March 2013 and validated with on the survey data for the month April 2013. Whole process of model implementation including training and validation is accomplished in the following steps. Data collection from survey at different transit stations for different time periods. ANFIS toolbox in MATLAB is used to train the model for one data set of the month February 2013 and then The model parameters are modified using the second data set of the month March 2013 and Finally the mode model result is validated using data set of the month April 2013. The model is implemented using Adaptive Neural fuzzy Inference System for peak period of work trips in Delhi urban area. The machine learning result is found quite satisfactory with validation error being as low as 0.68%. 6. Data Collection Data on house hold population and socio-economic activities such as commercial centers, Government offices, educational institutions, and health care system were collected from Delhi Transport Corporation, Delhi Development Authority, Municipal Corporation of Delhi, C.R.R.I. (Central Road Research Institute) and also for data collection survey were conducted at transit stations where passengers have option for mode choice. 7. Implementation Result For empirical implementation of the trip production and attraction model Artificial Neural Network System (ANN) is used. While validation it was observed that the result produced by these models is very close to the actual data. The average error estimated during the validation trip production and attraction model phase is low and minimum error is only 0.8%. For empirical implementation of the trip distribution model Genetic Algorithm is used. Trip Distribution model is applied on the real set of data which gives acceptable solution which is easily applicable and compared with other models such as Linear Programming model as well. The result achieved from traditional Linear Programming Based Model is not up to the mark as the number of input variables increases linear programming based model gives infeasible solution. For empirical implementation of the proposed model Adaptive Neural Fuzzy Inference System (ANFIS) is used. While validation it was observed that the result produced by the model is very close to the survey data. The average error estimated during the validation phase is low and minimum error is only 0.68%. 8. Impact of Research The transportation system being multidisciplinary system requires integration and co-ordination of various agencies. This includes STA (State Transport Authority), PWD (Public Works Department), DTC (Delhi Transport Corporation), DDA (Delhi Development Authority) and DMRC (Delhi Metro Rail Corporation) as well. The following table shows the impact of research in academics and industry. 9. Chapter wise contents Chapter 1 This chapter introduces the research subject giving its background and developments in the last decades. The objective of the present research is stated in this chapter. Chapter 2 reviews the literature on different aspects of this study and presents the contribution by different researchers and deficiencies therein. Chapter 3 presents the methodology of the research in chronological order while describing the model hypothesis and formulation in detail. This chapter also includes the description of soft computing tools used in this research. Chapter 4 describes the formulation and empirical implementation of trip production and attraction analysis for Delhi Urban Area and computational results of this work are highlighted. Chapter 5 describes the formulation and empirical implementation of trip distribution analysis for Delhi Urban Area and computational results of this work are highlighted. Chapter 6 describes the formulation and empirical implementation of mode-choice behavior modelling for Delhi Urban Area .The computational results of this work are highlighted in this chapter. Chapter 7 highlights the comments and conclusion of the research work. This also highlights the utility of this research in industry and its future scope. 10. Bibliography [1]Rodrigue, J., Comtois, C. and Slack, B., (2006), â€Å"The Geography of Transport Systems†, Dept. of Economics Geography, Hofstra University [2]Delhi Transport. Delhi Govt. Retrieved 2014. [3]Anthony Chen et.al, â€Å"Forecasting Network Traffic for Small Communities in Utah†, Report No. UTC-1002, February 2012 [4]Dantzing, GB, 1951, Application of the simplex method to a transportation problem, Activity Analysis of production and allocation, TC. Doopmands(ed.), N.Y. Wiley [5]Peter Guller in SYNERGO, Planning Project Management Zurich, Switzerland. â€Å"Integration of Transport and Land- use planning in Japan: Relevant finding from Europe†, [6]Published in Workshop on Implementing sustainable Urban Travel Policies in Japan and other Asia-Pacific Countries, Tokyo, 2-3, March 2005. [7]Kiron Chatterjee Andrew Gordon 2006 , Transport in Great Britain in 2030, ELSEVIER Transport Policy Journal. [8]Levinson, David and Kumar, Ajay(1995) Activity, Travel, and the Allocation of Time, Journal of the American Planning Association [9]FHWA. Injuries to Pedestrians and Bicyclists: An Analysis Based on Hospital Emergency Department Data. Report No. FHWA-RD-99-078. Washington, DC: USDOT, 1999. [10]Wilmot et.al 2006, Modeling Hurricane Evacuation Traffic: Testing the Gravity and Intervening Opportunity Models as Models of Destination choice in Hurricane Evacuation, LTRC Project No. 03-1SS, State Project No. 736-99-1116, Louisiana Transportation Research Center. [11]Richter.et.al., Modelling Mode Choice in Passenger Transport with Integrated Hierarchical Information Integration Journal of Choice Modelling, 5(1), 2012, page no. 1-21 [12]Ekong Daniel et.al, Inter-Urban Trip Generation Models for the Urban Centers in AkwaIbom State, Nigeria, Journal of Civil and Environmental Research, Vol.3, 2013. 11. List of Publications Paper Title: ‘An Improved Modeling of Mode-Choice Behavior in Urban Areas Using Adaptive Neural Fuzzy Inference System’, is present and published in the proceeding of IEEE International Conference on â€Å"Computing for Sustainable Global Development 05-07 March 2014, New Delhi, published in IEEE Xplore. Paper Title: ‘Artificial Neural Network based model for traffic production and attraction: A case study of all the zones of Delhi Urban area ’, is present and published in the proceeding of IEEE International Conference on â€Å"Computing for Sustainable Global Development 05-07 March 2014, New Delhi, published in IEEE Xplore. Paper Title: ‘Trip distribution Model for Delhi Urban Area Using Genetic Algorithm’, is published in International Journal of Computer Engineering Science March 2012; Vol.2 Issue 3, page no.1-8. Paper Title: ‘A soft computing based model for traffic attraction: A case study of a segment of Delhi urban Area’ is published in Vision and Quest, Research Journal of Science Technology and Management, Issue Jan 2010, page no.42-46. Paper Title: ‘Traffic Generation Model for Delhi Urban Area Using Artificial Neural Network’, is published in BVICAM International Journal of Information Technology, December 2010; Vol.2 No.2, page no.239-244 and having impact factor 0.605. 1/12 (Shivendra Goel) Research Scholar, Shobhit University, Meerut.

Sylvia Plaths Mirror Essay -- Papers Sylvia Plath Poem Poetry Essays

Sylvia Plath's Mirror Sylvia Plath's "Mirror" offers a unique perspective on the attitudes of aging. "Mirror" displays tremendous insight and objectivity into the natural human behavior of growing older. Plath is able to emphasize the loneliness, hope, despair, and insecurity that awaits us through mankind's incessant addiction with reflection. "Mirror" expresses the problems associated with aging through terse comparisons between reality and desire. Plathe's strength of "Mirror" lies in its ability to establish a solid comparison among appearance and human emotions between the first and second stanzas. At first "Mirror" introduces reflection as a precise and accurate force through utilizing the first person perspective of a mirror: "I am silver and exact. I have no preconceptions. Whatever I see I swallow immediately Just as it is, unmisted by love or dislike. I am not cruel, only truthful.." (Plathe lines 1-4) This example can then be viewed symbolically of appearance especially concerning "love or dislike". In that people never hate nor adore their features but merely accept that what they see is what defines them. This faith is reinforced by the quality and type of reflection because it is originating from a mirror which is suppose to be exact, honest, and universal for all. Plathe understanding these principles describes the reflection process by instilling this object with living characteristics such as thought, sight, and a lifestyle: "Most of the time I meditate on the opposite wall. It is pink with speckles. I have looked at it so long I think it is part of my heartà ¢? ¦Faces and darkness separate us over and over." (Pl... ... that not only destroys our reflection but also ones sense of identity, purpose, and confidence. The critical comparisons found in Sylvia Plath's "mirror" portray a distinctive attitude towards aging. Through contrasting the two separate stanzas the messages of desire, reality, individuality, fear, and insecurity are all demonstrated. Once the essence of Plathe's attitude is unlocked in "mirror" the emotion behind the writing is seen as the motivation for a tone that displays intense longing or weariness towards life. This becomes epitomized throughout Plathe's presentation as it utilizes age as a catalyst for the deterioration of the human spirit. Works Cited: Plath, Sylvia. ?Mirror.? The Language of Literature: American Literature. Eds. Arthur N. Applebee et al. Evanston: McDougal Littel, 1997. 252.

How Spongebob Effects The Brain

Pants, the wildly popular Nickelodeon has been under buzz as the cheerful, buzzing sponge can threaten a child's normal development. After much research, studies have shows that the television program has many characteristics that would make a child perform half as well as a child watching a public access cartoon. The every 1 1 second scene change during the T. V show doesn't defend the case anymore, as that causes mass confusion amongst the kids.Aiding to the case Is the total anta education message portrayed, thus making this show blindsided. The plebeian conundrum of the program has created a mass boom amongst a child who enjoys watching this show and also the countless medical professionals who are trying to dissuade parents. Research and countless studies have shown that 4 year olds who have watched nine minutes of Sponge, preformed only half as well as the children who spent the same amount of watching Callous which is a PBS show or drawing.This conundrum Is stated when head re searcher Brown stated â€Å"Technology is great, but we also want to explore how does that impact our 38) When the children are asked to perform four tasks such as playing games that involve rules, the non Sponge watching kids did significantly worse than the children that did not partake in the watching of the show. Eleven seconds doesn't seem Like a long time but It Is plenty of time to ruin a child's thinking capability.According to Christians, a professor of psychology at the university of Washington ; Sponge Squarest' constant rate of the program has a negative and a permanent detrimental effect on the wellbeing of the children. During a single nine minute episode, has over 30 changes with a very fast speed that leave the kids confused causing them to zone out or spun up. This is making the researchers think that the slower(but less amusing shows) that have about 2 changes per episode to be much better for the health of the children.Unlike Dora and Sesame Street which teach th e viewers how to read and write, Sponge entertains the children using utter stupidity and unrealistic motions. This shows children the negative behavior that they should not be portraying in the real life atmosphere. Many child psychologists state that there should be a educational factor that would aid In the learning of the children and also have a factor that can aka the children learn positive behavior.This show Is a negative role model for children as they are like clay, the way they are molded, is the way they will be. The negative harm that this show can cause on children is undetermined. There are many that state that this could be a permanent reaction while many state that this is a short lived reaction but all say that there Is a negative prospect of watching reactions that this would have, but there are some that are positive such as the lack of performance, confusion and of course bad habits. This would be a problem that can have countless problems yet to come.

Civil Disobedience by Henry David Thoreau - 1260 Words

Civil Disobedience was written by Henry David Thoreau. The Letter From A Birmingham Jail was written by Martin Luther King Jr. They both had similarities and differences. There were injustices that were done wrong to each of them by others in the society in which they both lived. The injustices and civil disobedience they incurred should never happen to anyone. Henry David Thoreau spoke in an emotional tone in his essay â€Å"Civil Disobedience.† The emotional part of his essay of Civil Disobedience is that he wants the people to speak up about what type of government they would want to have. Another emotional part was when he started to tell the people to stop paying their taxes so that if the government doesn’t get what they want then†¦show more content†¦This is racism and it is wrong and it is an injustice that the colored people had to face and deal with for many, many years. Martin Luther King Jr loves the church and wants the blacks to be included in everything that white people are. He was grateful to one reverend for including the black people in a Sunday service in a non-segregated way because it was the right thing to do. Segregation has been an injustice that many people have had to deal with for too many years. An ethical appeal that Martin Luther King Jr. was arguing about were the injustices that colored people face each day of their lives. He was arguing about what was right and what was wrong. He wanted people to realize that they were â€Å"victims of a broken promise†. They were promised that racial signs would be removed but they were not. He was using a non-violent direct action protest and got arrested for it because the whites kept the black people out of everything. The black people were being segregated and not allowed the same rights and courtesies as the white people. Colored people had a separate bathroom than the white people. 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