Trip generation is the first phase in the travel forecasting process. It involves the estimation of the
total number of trips entering or leaving a parcel of land per time period (usually on a daily basis);
as a function of the socioeconomic, locational, and land-use characteristics of the parcel.
The objective of this study is to develop statistical models to predict trips production volumes for a
proper target year. Non-motorized trips are considered in the modeling process. Traditional method
to forecast the trip generation volume according to trip rate, based on family type is proposed in
this study. Families are classified by three characteristics of population social class, income, and
number of vehicle ownership. The study area is divided into 10 sectors. Each sector is subdivided
into number of zones so; the total number of zones is 45 zones based on the administrative
divisions. The trip rate for the family is determined by sampling. A questionnaire is designed and
interviews are implemented for data collection from selected zones at Al-Karkh side of Baghdad
city. Two techniques have been used, full interview and home questionnaire. The questionnaire
forms are distributed in many institutes, intermediate, secondary and, commercial schools. The
developed models are total person trips /household, work trips /household, education trips/household, shopping and social/recreational trips/household and, person trips/person. These models are developed by using stepwise regression technique after the collected data being fed to SPSS software.
Results show that total persons trips/household are related to family size and structure variables
such as number of person more than 6 year age, number of male, total number of workers, total
number of students in the household, number of private vehicles. This model has coefficient of
determination equal to 0.669 for the whole study area. Also the results show that the home-based
work trips are related to number of worker in the household, number of male workers in the
household, number of female workers in the household and number of persons of (25-60) year age;
this model has coefficient of determination equal to 0.82 for the whole study area. Home-based
education trips are strongly related to number of students in the household and this model has
coefficient of determination equal to 0.90 for the whole study area
Tigris River water that comes from Turkey represents the main water resource of this river in Iraq. The expansion in water river implementations has formed a source of trouble for the workers in the water resources management field in Iraqi. Unfortunately, there is no agreement between Iraq and Turkey till now to share the water of this international river. Consequently, the optimal operation of water resources systems, particularly a multi-objective, multi-reservoir, is of the most necessity at the present time.
In this research two approaches, were used the dynamic programming (DP) approach and simulation model to find the optimal monthly operation of Ilisu Dam (from an Iraqi point of view) through a comp
... Show MoreThe purpose of this paper is to define fuzzy subspaces for fuzzy space of orderings and we prove some results about this definition in which it leads to a lot of new results on fuzzy space of orderings. Also we define the sum and product over such spaces such that: If f = < a1,…,an > and g = < b1,…bm>, their sum and product are f + g = < a1…,an, b1, …, bm> and f × g =
Recently, complementary perfect corona domination in graphs was introduced. A dominating set S of a graph G is said to be a complementary perfect corona dominating set (CPCD – set) if each vertex in is either a pendent vertex or a support vertex and has a perfect matching. The minimum cardinality of a complementary perfect corona dominating set is called the complementary perfect corona domination number and is denoted by . In this paper, our parameter hasbeen discussed for power graphs of path and cycle.
numerical study is applied to the mercury-argon mixture by solving the boltzman transport equation for different mixture percentage.