公开(公告)号：US20130324154A1

公开(公告)日：2013-12-05

申请号：US13909977

申请日：2013-06-04

Applicant: Arun Raghupathy ,  Ganesh Pattabiraman ,  Kumar Shubham ,  Henry Clark ,  Andrew Sendonaris ,  Steven J. Willhoff

Inventor： Arun Raghupathy ,  Ganesh Pattabiraman ,  Kumar Shubham ,  Henry Clark ,  Andrew Sendonaris ,  Steven J. Willhoff

IPC: H04W4/02

CPC classification number: G01S19/46 ,  G01S5/0236 ,  G01S19/10 ,  G01S19/42 ,  G01S19/52 ,  H04W4/02 ,  H04W4/025 ,  H04W64/00

Abstract: Devices, systems, and methods for gathering, calculating and sending positioning information at a user device to one or more networks may be disclosed. In a first implementation the user device transforms pseudorange information relating to terrestrial beacons into GNSS pseudorange information. In a second implementation, the user device sends position information using GNSS information elements. In a third implementation, the user device sends position information using non-GNSS information elements.

Abstract translation: 可以公开用于在用户设备处收集，计算和发送定位信息到一个或多个网络的设备，系统和方法。 在第一实现中，用户设备将与陆地信标相关的伪距信息转换成GNSS伪距信息。 在第二实施例中，用户设备使用GNSS信息元素发送位置信息。 在第三实施方式中，用户设备使用非GNSS信息元素发送位置信息。

公开(公告)号：US20230401454A1

公开(公告)日：2023-12-14

申请号：US18164505

申请日：2023-02-03

Applicant: Nikhil Pachauri ,  Chang Wook Ahn ,  Saurabh Agarwal ,  Tushar Bhardwaj ,  Gaurav Mishra ,  Kumar Shubham ,  Manoj Kumar Tiwari ,  Yagyadatta Goswami

Inventor： Nikhil Pachauri ,  Chang Wook Ahn ,  Saurabh Agarwal ,  Tushar Bhardwaj ,  Gaurav Mishra ,  Kumar Shubham ,  Manoj Kumar Tiwari ,  Yagyadatta Goswami

IPC: G06N5/02 ,  G05B15/02

CPC classification number: G06N5/02 ,  G05B15/02

Abstract: A method using weighted aggregated ensemble model for energy demand management of buildings includes initializing data values for integrated model to measure energy consumption, perform statistical analysis on data values to estimate accurate prediction, optimizing the data values using marine predator optimization for integrated model, analyze the output to minimize the mean square error and results show improvement in accuracy of integrated model. The data values comprise of σ, maximum number of splits, minimum leaf size, and λ. The weighted aggregated ensemble model for energy demand management of buildings shows best performance compared with other predictive models such as linear regression (LR), support vector regression (SVR), multilayer perceptron neural network (MLPNN), decision tree (DT), and generalized additive model (GAM).