12 papers · ranked by Valyu relevance
Liqing Xiao
Parameter tuning of PID controller for liquid level control of beer filling machine was studied in this paper, which can meet the demand of accurate controlling in beer production and improve the rapidity under the same conditions. Firstly, an improved genetic algorithm was proposed which has been verified by eight…
Zenghua Chen, Lingjian Zhu, He Lu, Shichao Chen + 4 more
'Sheng Liu' 'Yunjun Han' 'Gang Xiong'] Health monitoring and fault diagnosis of rolling bearings are crucial for the continuous and effective operation of mechanical equipment. In order to improve the accuracy of BP neural network in fault diagnosis of rolling bearings, a feature model is established from the vibration…
Dingming Yang, Zeyu Yu, Hongqiang Yuan, Yanrong Cui
Dingming Yang 202071544@yangtzeu.edu.cn School of Computer Science, Yangtze University, Jingzhou, 434023, China Zeyu Yu yuzeyu jz@163.com School of Electronic & Information, Yangtze University, Jingzhou, 434023, China Hongqiang Yuan 429809060@qq.com School of Urban Construction, Yangtze University, Jingzhou, 434000…
Ahmed Redha Mahlous, Houssam Mahlous, Yilun Shang
Universities face a constant challenge when distributing students and allocating them to their required classes, especially for a large mass of students. Generating feasible timetables is a strenuous task that requires plenty of resources, which makes it impractical to take student preferences into consideration during…
Mohd Nadhir Ab Wahab, Samia Nefti-Meziani, Adham Atyabi, Catalin Buiu
'Catalin Buiu'] Many swarm optimization algorithms have been introduced since the early 60’s, Evolutionary Programming to the most recent, Grey Wolf Optimization. All of these algorithms have demonstrated their potential to solve many optimization problems. This paper provides an in-depth survey of well-known…
Monique Simplicio Viana, Rodrigo Colnago Contreras, Orides Morandin Junior, Viorel Minzu
Job Shop Scheduling is currently one of the most addressed planning and scheduling optimization problems in the field. Due to its complexity, as it belongs to the NP-Hard class of problems, meta-heuristics are one of the most commonly used approaches in its resolution, with Genetic Algorithms being one of the most…
Majid Sohrabi, Amir M. Fathollahi-Fard, Vasilii A. Gromov
> Abstract. Genetic Algorithms (GAs) are known for their efficiency in solving combinatorial optimization problems, thanks to their ability to explore diverse solution spaces, handle various representations, exploit parallelism, preserve good solutions, adapt to changing dynamics, handle combinatorial diversity, and…
Okezue Bell
In recent years, optimization problems have become increasingly more prevalent due to the need for more powerful computational methods. With the more recent advent of technology such as artificial intelligence, new metaheuristics are needed that enhance the capabilities of classical algorithms. More recently…
Gonçalo Abreu, Rui Neves, Nuno Horta
Technical analysis is used to discover investment opportunities. To test this hypothesis we propose an hybrid system using machine learning techniques together with genetic algorithms. Using technical analysis there are more ways to represent a currency exchange time series than the ones it is possible to test…
E. Osaba, R. Carballedo, F. Diaz, E. Onieva + 2 more
'A. Perallos'] Since their first formulation, genetic algorithms (GAs) have been one of the most widely used techniques to solve combinatorial optimization problems. The basic structure of the GAs is known by the scientific community, and thanks to their easy application and good performance, GAs are the focus of a lot…
Denny Hermawanto
Genetic algorithm developed by Goldberg was inspired by Darwin's theory of evolution which states that the survival of an organism is affected by rule "the strongest species that survives". Darwin also stated that the survival of an organism can be maintained through the process of reproduction, crossover and mutation.…
Waleed Bin Owais, Iyad W. J. Alkhazendar, Mohammad Saleh
Genetic Algorithm is an evolutionary algorithm and a metaheuristic that was introduced to overcome the failure of gradient based method in solving the optimization and search problems. The purpose of this paper is to evaluate the impact on the convergence of Genetic Algorithm vis-a'-vis 0/1 knapsack. By keeping the…