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C Programming
Published in Paul W. Ross, The Handbook of Software for Engineers and Scientists, 2018
Function definitions cannot be nested. In many programming languages, nested function definitions are used to achieve some degree of structure and “information hiding.” That is, the details of a complicated algorithm can be organized into submodules whose details are hidden away inside the function. In this way, users of the algorithm will not be affected by any changes to the implementation details of these submodules. C can achieve some of the same benefits from the use of nested blocks, and through separate files. Remember that a block in C is a collection of statements that is surrounded by braces. A statement block can appear anywhere that a statement is valid. Thus, blocks can be nested. Variables can be declared at the beginning of a block. Their scope is from the point of declaration until the closing brace of that block. However, blocks are not named and cannot have parameters.
Passenger flow control with multi-station coordination in subway networks: algorithm development and real-world case study
Published in Transportmetrica B: Transport Dynamics, 2019
Xinyue Xu, Haiying Li, Jun Liu, Bin Ran, Lingqiao Qin
Consider a particular path with starting time interval k, which consists of a set of consecutive links, m1, m2, … ,mI, that is, . Note that the first link must be an access queuing link of origin station , and the last link must be an egress link of destination station . The travel time required by passengers departing from their origin during interval k to traverse a path can be computed by using the following nested function (Ran and Boyce 1996; Long et al. 2015): where , … , for short. Note that there are three types of different link functions, which are given as follows:
Circular Economy Model for Elderly Tourism Operation Based on Multi-source Heterogeneous Data Integration
Published in Applied Artificial Intelligence, 2023
Equation (1) is to calculate the state of change of the model expectation as the random value changes. Equation (2) is to calculate the change in the value of the nested function, and Equation (3) is to calculate the state of change in the output of the model output layer.
Dynamic traffic assignment in degradable networks: paradoxes and formulations with stochastic link transmission model
Published in Transportmetrica B: Transport Dynamics, 2019
Jiancheng Long, W. Y. Szeto, Jianxun Ding
We can obtain link cumulative flows and route cumulative flows from the procedure of DNL. Then, we can either directly retrieve route travel times from route cumulative flow curves (e.g. Lo and Szeto 2002; Szeto and Lo 2004, 2006; Long, Huang, and Gao 2013a) or indirectly deduce route travel times from link travel times that are derived from link cumulative flow curves (e.g. Long, Gao, and Szeto 2011; Long et al. 2015a). To explain the latter, we consider vehicles departing during time interval k and traveling through path . Their travel time on link is , and the time instant for leaving link and entering link is (which may not be an integer). Then, their travel time on link is , and the time instant for leaving link and entering link is . Similarly, we can obtain their travel times on other links. The route travel time of vehicles entering path during time interval k is equal to the sum of travel times on each link on that path, and can be computed by the following nested function: where , for short. In Equation (1), link travel times at both integer time instant and non-integer time instants are required to formulate path travel times. A linear interpolation procedure is applied to calculate the link travel times at non-integer time instants from link travel times at integer time instants. Link travel time at an integer time instant, which is numerically equivalent to link travel time associated with a particular time interval because , can be obtained from link cumulative flow curves (e.g. Long, Gao, and Szeto 2011; Long et al. 2015a) by, for example, the step function (SF) approach (see Long, Gao, and Szeto 2011 for details). If time is discretized, there is no guarantee that the traffic volume entering a link during a time interval will exit this link during the same time interval. For the SF-approach, the link travel time associated with a particular time interval is defined as the average link travel time of traffic volume entering the link during that interval.