scholarly journals Planning an Optimal Road Trip Analysis and Drowsiness Detection using Genetic Algorithm

2021 ◽  
Vol 9 (VI) ◽  
pp. 675-680
Author(s):  
Kajal Khatri
Keyword(s):  
Machine Learning ◽  
Genetic Algorithm ◽  
Global Search ◽  
Forecasting Model ◽  
Trip Generation ◽  
Road Trip ◽  
Drowsiness Detection ◽  
The Road ◽  
Learning Projects

One of the Machine Learning Projects which can promptly affect our lives is the Road Trip Analyzer. With our reliance on information and applications these days, going to new places has become the space of the excursion analyser. A solid Trip-generation Forecasting Model is the most essential piece of the traffic determining model. The undertaking has been based on the genetic algorithm which has extraordinary Worldwide Global search ability. It will permit the trip-generation forecasting model to improve the exactness of the expectation. Perhaps the greatest trouble in arranging an excursion is choosing where to stop en route. The proposed framework endeavours to coordinate with the drivers' requirement with the quickest course accessible so the clients have the smartest possible solution.

Machine Learning Accelerated Genetic Algorithms for Computational Materials Search

2018 ◽  
Author(s):  
Steen Lysgaard ◽  
Paul C. Jennings ◽  
Jens Strabo Hummelshøj ◽  
Thomas Bligaard ◽  
Tejs Vegge
Keyword(s):  
Machine Learning ◽  
Genetic Algorithm ◽  
Genetic Algorithms ◽  
Au Nanoparticles ◽  
Learning Model ◽  
Energy Calculations ◽  
Atomic Distribution ◽  
Machine Learning Model ◽  
Fold Reduction ◽  
Computational Materials

A machine learning model is used as a surrogate fitness evaluator in a genetic algorithm (GA) optimization of the atomic distribution of Pt-Au nanoparticles. The machine learning accelerated genetic algorithm (MLaGA) yields a 50-fold reduction of required energy calculations compared to a traditional GA.

Epileptic seizures classification in EEG using PCA based genetic algorithm through machine learning

2021 ◽  
Author(s):  
Md Khurram Monir Rabby ◽  
A. K. M. Kamrul Islam ◽  
Saeid Belkasim ◽  
Marwan U Bikdash
Keyword(s):  
Machine Learning ◽  
Genetic Algorithm ◽  
Epileptic Seizures

Story and Task Issue Analysis for Agile Machine Learning Projects

2020 ◽  
Author(s):  
Kushal Singla ◽  
T.M. Vinayak ◽  
A.S. Arpitha ◽  
Chetan Naik ◽  
Joy Bose
Keyword(s):  
Machine Learning ◽  
Learning Projects ◽  
And Task ◽  
Issue Analysis

A novel forecasting model for wind speed assessment using sentinel family satellites images and machine learning method

2021 ◽  
Author(s):  
M. Majidi Nezhad ◽  
A. Heydari ◽  
E. Pirshayan ◽  
D. Groppi ◽  
D. Astiaso Garcia
Keyword(s):  
Machine Learning ◽  
Wind Speed ◽  
Forecasting Model ◽  
Machine Learning Method ◽  
Learning Method

Simulation of English text recognition model based on ant colony algorithm and genetic algorithm

2021 ◽  
pp. 1-12
Author(s):  
Fei Long
Keyword(s):  
Machine Learning ◽  
Genetic Algorithm ◽  
Ant Colony Algorithm ◽  
Ant Colony ◽  
Text Recognition ◽  
English Text ◽  
Recognition Model ◽  
Central Node ◽  
Model Based ◽  
Characteristic Points

The difficulty of English text recognition lies in fuzzy image text classification and part-of-speech classification. Traditional models have a high error rate in English text recognition. In order to improve the effect of English text recognition, guided by machine learning ideas, this paper combines ant colony algorithm and genetic algorithm to construct an English text recognition model based on machine learning. Moreover, based on the characteristics of ant colony intelligent algorithm optimization, a method of using ant colony algorithm to solve the central node is proposed. In addition, this paper uses the ant colony algorithm to obtain the characteristic points in the study area and determine a reasonable number, and then combine the uniform grid to select some non-characteristic points as the central node of the core function, and finally use the central node with a reasonable distribution for modeling. Finally, this paper designs experiments to verify the performance of the model constructed in this paper and combines mathematical statistics to visually display the experimental results using tables and graphs. The research results show that the performance of the model constructed in this paper is good.

Lane Detection Algorithm Based on Genetic Algorithm and its Parallel Computing Realization

2012 ◽  
Vol 479-481 ◽  
pp. 65-70
Author(s):  
Xiao Hui Zhang ◽  
Liu Qing ◽  
Mu Li
Keyword(s):  
Genetic Algorithm ◽  
Data Transmission ◽  
High Speed ◽  
High Performance ◽  
Large Data ◽  
Detection Algorithm ◽  
Lane Detection ◽  
The Road ◽  
Time Problem ◽  
High Speed Data

Based on the target detection of alignment template, the paper designs a lane alignment template by using correlation matching method, and combines with genetic algorithm for template stochastic matching and optimization to realize the lane detection. In order to solve the real-time problem of lane detection algorithm based on genetic algorithm, this paper uses the high performance multi-core DSP chip TMS320C6474 as the core, combines with high-speed data transmission technology of Rapid10, realizes the hardware parallel processing of the lane detection algorithm. By Rapid10 bus, the data transmission speed between the DSP and the DSP can reach 3.125Gbps, it basically realizes transmission without delay, and thereby solves the high speed transmission of the large data quantity between processor. The experimental results show that, no matter the calculated lane line, or the running time is better than the single DSP and PC at the parallel C6474 platform. In addition, the road detection is accurate and reliable, and it has good robustness.

An Integrated Framework for Driver Drowsiness Detection and Alcohol Intoxication using Machine Learning

2021 ◽  
Author(s):  
Renju Rachel Varghese ◽  
Pramod Mathew Jacob ◽  
Joanna Jacob ◽  
Merlin Nissi Babu ◽  
Rupali Ravikanth ◽  
...  
Keyword(s):  
Machine Learning ◽  
Alcohol Intoxication ◽  
Integrated Framework ◽  
Drowsiness Detection ◽  
Driver Drowsiness
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