8 results about "Arrival time" patented technology

The invention provides a bus arrival time prediction system and method based on multi-user cooperation. The system comprises a plurality of pieces of intelligent mobile equipment and a background server. The method comprises the following steps: a plurality of users position the geographic positions of the users in real time through the intelligent mobile equipment; the background server performs positioning on the basis of a bus route; the background server performs arrival time prediction; the background server performs arrival time prediction result correction; an arrival time prediction result is displayed on the intelligent mobile equipment in real time, and the current relative positions of the users on the bus route are displayed to the users in real time; when the users arrive at target bus stations, corresponding intelligent mobile equipment stops submitting the geographic position information to the background server. The intelligent mobile terminal is adopted instead of professional equipment, so that the implementation cost is lowered; data is acquired for analysis in a multi-user cooperation way in the running process of a bus, and the bus arrival time is dynamically predicted in real time, so that the system and the method have the characteristics of easiness in use and protection of user privacy.

The invention discloses a simulation method for a random signal sequence. The method can simulate photon fluctuation information and arbitrary random process signal, and can rapidly realize long-term high precision simulation of photon arrival time. The method includes: step 1. making use of the photon flow function of a to-be-simulated signal to deduce a photon number distribution function; step 2. according to the characteristic that the photon number distribution function satisfies uniform distribution, making use of the uniformly distributed function to generate a random number, thereby obtaining a random number of the photon number; step 3. utilizing the random distribution satisfied by the photon number fluctuation, taking a random variable satisfying the random distribution within an observation period to serve as the number of times Nf that the photon is detected within an observation period; step 4. repeating the step 2 Nf times, thus obtaining Nf random numbers of the photon number; and step 5. utilizing the inverse function of the photon number distribution function to perform inverse function conversion on the Nf random numbers, thus obtaining Nf random numbers of the photon arrival time, and conducting sorting by sized, thus obtaining a random sequence of the photon arrival time.

The invention provides an automatic control device and an automatic control system for a casement aluminum alloy window, which belong to the field of daily life. The automatic control device includes: a position sensor used to detect whether the current home window is in a closed state, and used to control the opening and closing of the window The execution module, the information interaction module for environmental weather conditions and time detection, the core control module for interacting with the external weather and time according to the current position sensor, the core control module controls the execution module when it reaches the set time and when it rains suddenly Proceed to close the windows. The automatic control system provided by the present invention includes an automatic control device and a remote user module. The remote user module can allow the user to control the execution module to open or close the window in real time, and feedback the weather conditions of the current user's residence and the next 24 hours so that the user can reasonably Select the time to open the window for ventilation. The solution provided by the invention can prevent rain, ventilate and avoid refitting windows.

The invention discloses an intercity transportation dispatching method and an intercity transportation dispatching system on the basis of artificial intelligence. The intercity transportation dispatching method includes acquiring travel information of users; formulating a plurality of travel schemes to be selected by the users; making appointments with to-be-taken vehicles according to the travelschemes selected by the users; paying corresponding vehicle expenses; allowing the users to arrive at departure places to take the vehicles according to the appointment time. The travel information comprises the departure places, destinations, the arrival time, the payment capacity and the preferable vehicles. Each travel scheme includes three phases, the first phase is departure place intracity phase, the second phase is an intercity phase, and the third phase is a destination city phase. The intercity transportation dispatching method and the intercity transportation dispatching system havethe advantages that the problem that existing users need to voluntarily plan journeys and purchase tickets during intercity travel can be solved, the travel efficiency can be greatly improved, and thetravel time can be saved.

The invention provides a real-time interval transit time extraction method based on particle swarm optimization, mainly to solve the problems of large amount of operation and low precision in the caseof interval transit time calculation by the traditional STC algorithm. The realization process comprises steps: (1) ranges of first wave arrival time and interval transit time of a certain mode waveare given; (2) a population is initialized; (3) the fitness value of a particle is calculated; (4) the historical highest fitness value of the particle and the global historical highest fitness valueof the population are updated; (5) the position of the particle is updated; and (6) whether the algorithm meets an end condition is judged, and if yes, iteration is stopped, or otherwise, the step (3)is carried out. The particle swarm optimization algorithm based on population random search is adopted for interval transit time extraction, traversal search of time and slowness is not needed, the algorithm is the global optimization method, the amount of operation of a program is greatly reduced, and the formation interval transit time can be quickly and accurately extracted.

The invention discloses a logistics transportation planning method and system and a computer readable storage medium, and the method comprises the steps: receiving a goods collection instruction transmitted by a logistics server, and obtaining the GPS data of a truck, so as to achieve the real-time positioning of the truck; when the positioning position of the truck does not reach the specified safety area, acquiring a historical transportation record from a logistics server, and deducing an expected time interval when the truck reaches the specified safety area in real time according to the historical transportation record and the positioning position of the truck; and sending the predicted time interval to a supplier corresponding to the specified security area to prompt the supplier tofinish stock preparation before the predicted time interval. According to the invention, the estimated arrival time interval of the truck can be determined through the positioning position of the truck and the historical transportation record of the truck, so that a supplier can control the production progress according to the estimated arrival time interval, and the problems of transportation delivery delay and time cost waste of a logistics company caused by untimely production of goods are prevented.

The invention provides an unknown wave velocity acoustic emission source positioning method and system based on an improved MSAC algorithm. The method comprises the following steps of: firstly, non-repeatedly selecting at least five arrival times required by positioning from n arrival time data to form an arrival time subset, and calculating an acoustic emission parameter according to the arrival time subset; calculating estimated values of all arrival time data according to the acoustic emission parameter, and obtaining absolute deviation between the arrival time and the estimated values; when the absolute deviation is smaller than a specified threshold, classifying the corresponding arrival time into a consistent set; calculating the score of the consistent set, and if the score of the consistent set is the highest at present, performing local optimization; repeating the steps until the number of times of operation reaches the specified number of times of operation; and performing repositioning according to all the arrival time data of the arrival time consistent set with the highest score to obtain an optimal positioning result. According to the method, the abnormal arrival time can be identified and eliminated more accurately, the positioning precision is improved, and the calculation efficiency is high.