Nt1330 Unit 4 Agression Analysis Paper

This produces a 106% error causing a very large range of possible values causing our results to be very imprecise.

The national aviation system is under increasing demand for more and more flights as air passenger numbers continue to rise. The Federal Aviation Administration (FAA) Aerospace Forecast Fiscal Years 2015-2035 report estimates an annual growth of 2.0 percent per year from 2016-2035. This will equate to an average of 1.14 billion passengers flying within the U.S. per year by the end of year 2035 (n.d., p. 47). As the number of aircraft flying increase to accommodate passenger demand, the number of aircraft delays and risk to flight safety are also likely to increase. The current air traffic control (ATC) infrastructure evolved from the World War II era and wasn’t designed to handle the predicted air traffic loads of the 21st century (Hopkin, Wise & Garland, 2010). In order to update the ATC system to increase its capacity, the FAA, along with other select governing bodies have started implementing NextGen.

Aviation has come a long way since the days when safe operation between aircraft was based purely on the 'SEE AND BE SEEN' principle. With the aircraft closing speeds in excess of 1000 mph, and increasing density of air traffic, the impracticability of reliance upon such a system is obvious.

account a wide variety of loads which may vary based on the duration of the load

Suggestion of a possible improvement and explanation of how this will improve the accuracy or precision of the

This performance not only meet the goal for the most part, but also show a relatively good outcomes comparing to other cases such as MAX in Utah, Rapid between San Pablo and Oakland in Boston especially in ridership increase. However, it still need improvement afterwards.

The results were repeated three times for an accurate average time and any "strange results" were repeated to improve accuracy.

“Chapter 5: Other Approaches to Reducing Delay.” Airport System Development. n.d. Web. 25 March 2014.

more pieces of redundant data in order to ensure we can correct s = 1 error.

2.3 Accuracy Comparison . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16

where, d = average control delay (s/veh), cm,x = capacity of movement or shared lane (veh/h), T = analysis period (h) and vx = demand flow rate for movement or shared lane (veh/h)

Although the model might seem as a complicated model for human calculation, the formula is simple in mathematical terms. Therefore, high-tech computer programs are not need to compute and it can also save time.

Also, since the results of the two ratios above are approximately same as predicted, the results support the

In order to evaluate the effectiveness of the proposed method, 3-unit, 30 Bus IEEE, 13-unit and 15-units are used as case studies with incremental fuel cost functions. The constraints include ramp rate limits, prohibited operating zones and the valve point effect. These constraints make the economic dispatch (ED) problem a non-convex minimization problem with constraints. Simulation results obtained by the proposed algorithm are compared with the results obtained using other methods available in the literature. Based on the numerical results, the proposed RTO algorithm is able to provide better solutions than other reported techniques in terms of fuel cost and robustness. In order to verify the feasibility and efficiency of the proposed algorithm, RTO algorithm was applied on two set of case studies. The first set includes a 23 standard benchmark functions. The second set includes four test systems (i.e., 3, 6, 13 and 15-units systems) for solving ED problem considering various constraints.

If not satisfied, it will reset the system parameters. This set value will primarily be determined to its ' initial value of PID controller. Every solved result is directly related to the previous operating parameter. The operation will get a group of optimal solutions or sub-optimal solutions by genetic algorithm, to run the relevant program in accordance with the related search algorithm. There is no system that will not stop, for the great waste of time and space resources. Every interval of time, the value is determined according to the actual needs of production environment. When the