Comparison of sonic boom rise time prediction techniques

1992 ◽  
Vol 91 (3) ◽  
pp. 1767-1768 ◽  
Author(s):  
Henry E. Bass ◽  
Richard Raspet
Keyword(s):  
Rise Time ◽  
Sonic Boom ◽  
Time Prediction ◽  
Prediction Techniques

Rise Time Prediction of Sonic Boom by Full-Field Simulation

2018 ◽  
Vol 55 (3) ◽  
pp. 1305-1310 ◽  
Author(s):  
Rei Yamashita ◽  
Kojiro Suzuki
Keyword(s):  
Rise Time ◽  
Sonic Boom ◽  
Full Field ◽  
Time Prediction ◽  
Field Simulation

scholarly journals Spatio-Temporal Check-in Time Prediction with Recurrent Neural Network based Survival Analysis

2018 ◽  
Author(s):  
Guolei Yang ◽  
Ying Cai ◽  
Chandan K Reddy
Keyword(s):  
Neural Network ◽  
Survival Analysis ◽  
Recurrent Neural Network ◽  
Censored Regression ◽  
Event Time ◽  
Time Prediction ◽  
Spatio Temporal ◽  
Latent Representations ◽  
Real World Datasets ◽  
Prediction Techniques

We introduce a novel check-in time prediction problem. The goal is to predict the time a user will check-in to a given location. We formulate check-in prediction as a survival analysis problem and propose a Recurrent-Censored Regression (RCR) model. We address the key challenge of check-in data scarcity, which is due to the uneven distribution of check-ins among users/locations. Our idea is to enrich the check-in data with potential visitors, i.e., users who have not visited the location before but are likely to do so. RCR uses recurrent neural network to learn latent representations from historical check-ins of both actual and potential visitors, which is then incorporated with censored regression to make predictions. Experiments show RCR outperforms state-of-the-art event time prediction techniques on real-world datasets.

Flight test measurements of the effect of turbulence on sonic boom peak overpressure and rise time

1992 ◽  
Vol 92 (4) ◽  
pp. 2329-2330
Author(s):  
William L. Willshire ◽  
Donald P. Garber ◽  
David W. DeVilbiss
Keyword(s):  
Rise Time ◽  
Flight Test ◽  
Sonic Boom

scholarly journals Sonic boom rise time

1994 ◽  
Vol 96 (5) ◽  
pp. 3275-3275 ◽  
Author(s):  
Robin O. Cleveland ◽  
David T. Blackstock
Keyword(s):  
Rise Time ◽  
Sonic Boom

Desain dan Komparasi Kontrol Kecepatan Motor DC

2020 ◽  
Vol 7 (2) ◽  
pp. 127-134
Author(s):  
Safah Tasya Aprilyani ◽  
Irianto Irianto ◽  
Epyk Sunarno
Keyword(s):  
Steady State ◽  
Rise Time ◽  
Settling Time ◽  
Proportional Integral

Penggunaan kontrol sangat diperlukan dalam pengaturan kecepatan motor DC. Dalam pengaturan kecepatan motor DC, salah satu jenis kontrol yang digunakan adalah kontrol Proportional Integral (PI). Untuk 4 jenis metode pada kontrol PI yang digunakan adalah metode Ziegler Nichole, Chien Servo 1, Chien Regulator 1 dan perhitungan secara analitik yang telah diperoleh dari data yang sudah ada.  Namun kontrol dengan PI 4 metode yang digunakan  sebagai pembanding memiliki waktu respon kecepatan saat stabil cenderung lambat baik dari nilai settling time, rise time dan steady state. Maka dari itu dilakukan komparasi antara 4 metode kontrol PI dengan penggunaan kontrol fuzzy. Dalam membandingkan antara 4 metode kontrol PI dan kontrol fuzzy terdapat beberapa parameter sebagai perbandingan yaitu maximum overshoot, steady state, rise time dan settling time. Hasil dari perbandingan tersebut adalah kontrol fuzzy dapat menghasilkan performa lebih baik jika dibandingkan dengan 4 metode pada kontrol PI. Kontrol fuzzy memiliki nilai rise time sebesar 0,015 detik, nilai settling time sebesar 0,025 detik dengan kecepatan sebesar 2900 rpm serta error steady state sebesar 3,33% tanpa adanya overshoot dan osilasi.

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