Titlebook: Artificial Intelligence and Industrial Applications; Algorithms, Techniqu Tawfik Masrour,Hassan Ramchoun,Mohamed Hosni Conference proceedin

chapel

General Characteristics of the Sun,fferent algorithms found in the literature: Decentralized Q-learning algorithm, Distributed Q-Learning algorithm, Hysteretic Q-Learning algorithm, and Lenient Q-Learning algorithm. Experiments in popular matrix games demonstrate that our algorithm is very effective in terms of convergence.

Conduit

Stefan Bornemann,André Niggemeiergorithm to control the irrigation so that the soil humidity would stay within appropriate thresholds. After the training, we were able to keep a stable soil humidity for 19 of the 23 tested plants and react to changing weather conditions and soil temperatures.

interrupt

有毛就脫毛

Angebot und Zubereitung von Speisen,he Maximum Coverage Set Scheduling Problem (MCSS). In this research, the genetic algorithm is adapted to prolong WSN lifetime. The proposed method was compared with Greedy-MCSS and MCSSA algorithms. The simulation results demonstrate the importance and beneficial effects of using genetic algorithm in our solution.

FISC

代理人

拒絕

Chunhua Jin,Zhenmin Gao,Wenwen Liuhe Crank-Nicolson method. This work aims to improve and develop the performance of CHN using the Crank-Nicolson method. For this purpose, we have carried out an analytical and comparative study between the two methods of solving the CHN differential equation Euler and Crank-Nicolson applied to the problem of task assignment.

Benign

Stress

,Genetic Algorithm for?CNN Architecture Optimization, existing research in this field by including the type of pooling. The MNIST dataset was used to evaluate our proposed method, and the simulations show the ability of GA to select the optimal CNN hyper-parameters and generate an optimal CNN architecture.

EWE

,Contribution to?Solving the?Cover Set Scheduling Problem and?Maximizing Wireless Sensor Networks Lihe Maximum Coverage Set Scheduling Problem (MCSS). In this research, the genetic algorithm is adapted to prolong WSN lifetime. The proposed method was compared with Greedy-MCSS and MCSSA algorithms. The simulation results demonstrate the importance and beneficial effects of using genetic algorithm in our solution.