Intelligent Algorithms for Movie Sound Tracks Restoration

Author(s):  
Andrzej Czyżewski ◽  
Marek Dziubiński ◽  
Łukasz Litwic ◽  
Przemysław Maziewski
2016 ◽  
Vol 6 (2) ◽  
pp. 199-216
Author(s):  
Safaai Bin Deris ◽  
Nazar Zaki

2011 ◽  
Vol 121-126 ◽  
pp. 4481-4485
Author(s):  
Ai Yu Zhang ◽  
Xiao Guang Zhao ◽  
Lei Zhang

Due to the limited generality of traditional fault diagnosis expert system and its low accuracy of extracting failure symptoms, a general fault monitoring and diagnosis expert system has been built. For different devices, users can build fault trees in an interactive way and then the fault trees will be saved as expert knowledge. A variety of sensors are fixed to monitor the real-time condition of the device and intelligent algorithms such as wavelet transform and neural network are used to assist the extraction of failure symptoms. On the basis of integration of multi-sensor failure symptoms, the fault diagnosis is realized through forward and backward reasoning. The simulation diagnosis experiments of NC device have shown the effectiveness of the proposed method.


2021 ◽  
Vol 19 (1) ◽  
pp. 011301
Author(s):  
Lifeng Ma ◽  
Jing Li ◽  
Zhouhui Liu ◽  
Yuxuan Zhang ◽  
Nianen Zhang ◽  
...  

Author(s):  
O.L. Cvetkova ◽  
◽  
A.R. Ajdinyan

Agricultural enterprises are interested in high-quality and low-cost plastering of technological and warehouse premises. It is proposed to solve the problem using mechatronic complexes intended for plastering surfaces characterized by different features of irregularities. The work considers intelligent algorithms for controlling the actions of a stucco robot based on the use of an artificial neural network. Intelligent algorithms will provide the formation of control actions for the robot when applying the mortar to the surface, with a rough leveling of the mortar layer, will allow solving the inverse kinematic problem of position for the plastering robot with less computational costs.


2013 ◽  
Vol 16 (2-03) ◽  
pp. 203-215 ◽  
Author(s):  
Danilo Pelusi ◽  
Massimo Tivegna ◽  
Pierluigi Ippoliti

Forests ◽  
2021 ◽  
Vol 12 (12) ◽  
pp. 1658
Author(s):  
Shuping Fang ◽  
Yu Ru ◽  
Yangyang Liu ◽  
Chenming Hu ◽  
Xuyang Chen ◽  
...  

It is of great value to research the problem of forest pest and disease control. Currently, helicopters play an important role in dealing with this problem. However, the spraying route planning still depends on the pilot’s driving experience, which leads to low efficiency and less accurate coverage. For this reason, this paper attempts to use intelligent algorithms to plan the pesticide spraying route for helicopters. When the helicopter is conducting spraying operations in multiple forest areas, the routes are divided into two parts: pesticide spraying routes for individual forest areas and dispatch routes between multiple forest areas. First, the shorter spraying route with fewer turnarounds for individual forest areas was determined. Then a two-layer intelligent algorithm, a combination of a genetic algorithm (GA) and ant colony optimization algorithm (ACO), was designed to determine the dispatch route between multiple forest areas, which is referred to as GAACO-GA. The performance was evaluated in self-created multiple forest areas and compared with other two-layer intelligent algorithms. The results show that the GAACO-GA algorithm found the shortest dispatch route (5032.75 m), which was 5.60%, 5.45%, 6.54%, and 4.07% shorter than that of GA-GA algorithm, simulated annealing-GA (SA-GA) algorithm, ACO-GA algorithm, and particle swarm optimization-GA (PSO-GA) algorithm, respectively. A spraying experiment with a helicopter was conducted near Pigzui Mountain, Huai’an City, Jiangsu Province, China. It was found that the flight path obtained from the proposed algorithm was 5.43% shorter than that derived from a manual planning method. The dispatch route length was reduced by 16.93%, the number of turnarounds was reduced by 11 times, and the redundant coverage was reduced by 17.87%. Moreover, helicopter fuel consumption and pesticide consumption decreased by 10.56% and 5.43%, respectively. The proposed algorithm can shorten the application route, reduce the number of turnarounds and the cost of spraying operations, and has the potential for use in spraying operations in smart forestry and agriculture.


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