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    MOBILE USER TRAJECTORY PREDICTION SYSTEM WITH EXTREME MACHINE LEARNING ALGORITHM
    51.
    发明专利
    MOBILE USER TRAJECTORY PREDICTION SYSTEM WITH EXTREME MACHINE LEARNING ALGORITHM 未知

    公开(公告)号：AU2021105525A4

    公开(公告)日：2021-11-11

    申请号：AU2021105525

    申请日：2021-08-15

    Applicant: AGRAWAL SANDEEP KUMAR ,  JAISWAL SUSHMA ,  JAISWAL TARUN ,  KALPANA G ,  KUMAR K R N KIRAN ,  L SATHISH KUMAR ,  MARAGANI SATISH KUMAR ,  RANI V VASUDHA ,  RAO CHENNAMSETTY MADHUSUDHANA ,  SARANGI SANJAYA KUMAR ,  SENTHILMURUGAN S ,  VASAVI G

    Inventor： KALPANA G ,  MARAGANI SATISH KUMAR ,  L SATHISH KUMAR ,  VASAVI G ,  RAO CHENNAMSETTY MADHUSUDHANA ,  RANI V VASUDHA ,  KUMAR K R N KIRAN ,  SARANGI SANJAYA KUMAR ,  AGRAWAL SANDEEP KUMAR ,  SENTHILMURUGAN S ,  JAISWAL TARUN ,  JAISWAL SUSHMA

    IPC: G06N3/02 ,  G05B13/02 ,  G06F3/048 ,  G06N20/00 ,  H04W4/029

    Abstract: MOBILE USER TRAJECTORY PREDICTION SYSTEM WITH EXTREME MACHINE LEARNING ALGORITHM The global adoption of smartphones and location-based services has resulted in a massive and rapid increase in Mobile User data. Because of the large size of Mobile User data, new possibilities for determining the characteristics of Mobile User mobility patterns and making mobility predictions emerge. Predicting mobile user mobility is critical in a variety of modern applications, including personalized recommendation systems and 5G networks. The present invention disclosed herein is Mobile User Trajectory Prediction System with Extreme Machine Learning Algorithm comprising of Trajectory Dataset (101), Extreme Machine Learning (102), Sequence to Sequence (103), Trajectory Prediction (104); can predict the trajectory of the mobile user with high accuracy and low mean square error. The present invention disclosed herein uses Extreme Machine Learning (EML) Algorithm with Sequence to Sequence (Seq2Seq) Algorithm. The EML with Seq2Seq can predict the trajectories by next locations prediction with training the trajectories of their previous locations of single or multiple mobiles users. Predicting location of users plays an important role for 5G Internet networks as network service providers need to allocate nearest resources to users to process their mobile request data. The present invention disclosed herein can achieves good accuracy in predicting the trajectory of the mobile user with low Mean Square Error (MSE) of 0.00776, compared with the other existing inventions such as Long Term Short Term Memory (LSTM) in which MSE is 1.85185 and Gate Recurrent Unit (GRU) with MSE of 11.89521. The present invention, EML with Seq2Seq disclosed herein is having mobile user prediction accuracy of 95.47%. The Geolife real life trajectory movement dataset which consist of user's movement latitude, longitude and users id with each mobile user has 9 locations are considered for training the proposed present invention. MOBILE USER TRAJECTORY PREDICTION SYSTEM WITH EXTREME MACHINE LEARNING ALGORITHM 101 102 103 104 TRAJECTORY EXTREME MACHINE SEQUENCE TO TRAJECTORY DATASET LEARNING SEQUENCE PREDICTION Figure 1: Mobile User Trajectory Prediction System with Extreme Machine Learning Algorithm. UPLOAD DATASET 202 GENERATE EML MODEL 203 r ENTER USER PREDICT TRAJECTORY GENERATE MSE GRAPH J.206 Figure 2: Flow Chart of the present Invention.

    Kablosuz güç.
    55.
    发明专利
    Kablosuz güç. 未知

    公开(公告)号：TR201900223T4

    公开(公告)日：2019-02-21

    申请号：TR201900223

    申请日：2011-08-13

    Applicant: SANDEEP KUMAR CHINTALA

    Inventor： SANDEEP KUMAR CHINTALA

    IPC: G06K7/10 ,  H02J5/00 ,  H02J7/02 ,  H02J50/12 ,  H02J50/23 ,  H02J50/80 ,  H04B5/00

    Abstract: Bir aparat (5) bir dizideki bitişik aparatlar (5) arasında veri ve enerji alabilir ve aktarabilir. Her bir aparat (5), bir kontrol devresindeki (18) bir alıcı ve demodülatöre (40) yönelik ayarlanan ve empedansı eşleştirilen (14) bir giriş sinyalinin (12) alınmasına yönelik bir giriş anteni (10) içerir. Demodüle edilmiş sinyal, bir çıkış sinyali (34) oluşturmak üzere bir verici modülüne (42) girdi olarak sağlanır. Giriş sinyalinin (12) akabinde bir bataryayı (26) şarj eden bir güç kaynağına (24) enerji sağlamak üzere yeterli bir voltaj üretmek üzere empedansı dönüştürülür. Giriş sinyali (12) ve çıkış sinyali (34) bir radyo sinyali, bir manyetik endüksiyon sinyali veya kombine bir radyo ve manyetik endüksiyon sinyali olabilir. Kontrol devresindeki (18) bir kontrol elemanı (38) bataryanın (26) durumunu ve güç kaynağını (24) gözlemler ve bunların gözlemlenmiş durumuna bağlı olarak seçmeli olarak aparatın (5) güç parçalarını çalıştırabilen bir anahtarı (44) kontrol eder.

    A SYSTEM TO GENERATE ELECTRICITY FROM SEA WAVE
    60.
    发明专利
    A SYSTEM TO GENERATE ELECTRICITY FROM SEA WAVE 未知

    公开(公告)号：IN1026DE2013A

    公开(公告)日：2015-07-10

    申请号：IN1026DE2013

    申请日：2013-04-05

    Applicant: SANDEEP KUMAR JAISWAL

    Inventor： SANDEEP KUMAR JAISWAL

    IPC: H01M20060101

    Abstract: This invention relates to a system to generate electricity from sea waves comprising an inclined platform mounted with a plurality of channels and openings, wherein a dam is positioned adjacent to the ramp for collecting water, which is used to generate electricity. I t is associated with the following advantageous features:- - Pollution free. - Cost effective. - Efficient. - Simple in construction. - Uses natural source of energy which is available as abundance. - Self functioning system.

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