It is well known that fixed point theorems have been widely applied to many areas such as mechanics, physics, transportation, control, economics, and optimization.
Besides NPPs, the proposed model can be applied to many other fields, e.g. aviation, air transportation control, driving and radar vigilance, etc.
NP also interacts with other viral proteins (PB1, PB2, and M1) and cellular proteins (Importin α, F-actin, CRM1/exportin1) for viral transcription control and nuclear transportation control [10].
WSNs have been widely used in military, environment monitoring, medicine care, and transportation control.
This paper illustrates some of the human performance concerns for novel transportation control systems that are faced today and discusses how this area of cognitive attention, human error and workload is difficult to assess and predict.
In this paper, an intelligent transportation control system (ITCS) using wavelet neural network (WNN) and proportional-integral-derivative-type (PID-type) learning algorithms is developed to increase the safety and efficiency in transportation process.
Its products are applied principally in automatic teller machines (ATMs), transportation control, buildings, schools, warehouses, shops, stations, airports, governments, hospitals and parking lots, among others.
As far as we know, this is the first energy-optimal solution for transportation control of underactuated double pendulum cranes with various state and control constraints.
Bi-level programming problems (BLPPs) arise very often in areas of engineering, transportation control.
Therefore, from a practical perspective, this paper proposes an energy-optimal solution for transportation control of double pendulum cranes.
