Robust reinforcement learning algorithm based on pigeon-inspired optimization by Mingying ZHANG, Bing HUA, Yuguang ZHANG, Haidong LI, Mohong ZHENG

“…Reinforcement learning(RL) is an artificial intelligence algorithm with the advantages of clear calculation logic and easy expansion of the model.Through interacting with the environment and maximizing value functions on the premise of obtaining little or no prior information, RL can optimize the performance of strategies and effectively reduce the complexity caused by physical models .The RL algorithm based on strategy gradient has been successfully applied in many fields such as intelligent image recognition, robot control and path planning for automatic driving.However, the highly sampling-dependent characteristics of RL determine that the training process needs a large number of samples to converge, and the accuracy of decision making is easily affected by slight interference that does not match with the simulation environment.Especially when RL is applied to the control field, it is difficult to prove the stability of the algorithm because the convergence of the algorithm cannot be guaranteed.Considering that swarm intelligence algorithm can solve complex problems through group cooperation and has the characteristics of self-organization and strong stability, it is an effective way to be used for improving the stability of RL model.The pigeon-inspired optimization algorithm in swarm intelligence was combined to improve RL based on strategy gradient.A RL algorithm based on pigeon-inspired optimization was proposed to solve the strategy gradient in order to maximize long-term future rewards.Adaptive function of pigeon-inspired optimization algorithm and RL were combined to estimate the advantages and disadvantages of strategies, avoid solving into an infinite loop, and improve the stability of the algorithm.A nonlinear two-wheel inverted pendulum robot control system was selected for simulation verification.The simulation results show that the RL algorithm based on pigeon-inspired optimization can improve the robustness of the system, reduce the computational cost, and reduce the algorithm’s dependence on the sample database.…”
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Comparative analysis of dehazing algorithms on real-world hazy images by Chaobing Zheng, Wenjian Ying, Qingping Hu

“…Neural augmentation algorithms, however, effectively combine the strengths of both approaches, offering a better overall solution. …”
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An intelligent algorithm to fast and accurately detect chaotic correlation dimension by Mengyan Shen, Miaomiao Ma, Zhicheng Su, Xuejun Zhang

“…Therefore, it is necessary to propose a fast and intelligent algorithm to solve the above problem. This study implies the distinct windows tracking technique and fuzzy C‐means clustering algorithm to accurately identify the scaling range and estimate the correlation dimension values. …”
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Examining the Efficiency of Learning-Based Algorithms in the Process of Declaring Customs by Mustafa Günerkan, Ender Şahinaslan, Önder Şahınaslan

“…Regarding the K-Fold method, which assumes K to be equal to 10, similar success rates were obtained for the Decision Tree (75.84%) and Bagging (75.83%) algorithms. These results reveal the use of machine learning algorithms to be an effective method for detecting notification errors. …”
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Water Quality Prediction Based on Hybrid Deep Learning Algorithm by Bhagavathi Perumal, Niveditha Rajarethinam, Anusuya Devi Velusamy, Venkatesa Prabhu Sundramurthy

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Chaotic Puma Optimizer Algorithm for controlling wheeled mobile robots by Mohamed Kmich, Nawal El Ghouate, Ahmed Bencharqui, Hicham Karmouni, Mhamed Sayyouri, S.S. Askar, Mohamed Abouhawwash

“…The control of wheeled mobile robots plays a crucial role in many fields, including automation, logistics, security, and even space exploration. …”
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Energy aware computer vision algorithm deployment on heterogeneous architectures by Teymoor Ali, Deepayan Bhowmik, Robert Nicol

“…Abstract Computer vision algorithms, specifically convolutional neural networks (CNNs) and feature extraction algorithms, have become increasingly pervasive in many vision tasks. …”
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A lightweight 256 hexadecimal character substitution Cipher algorithm by Ibrahim Lawal, Musa Yusuf, Adamu Sulaiman Usman, Oluwasegun Ishaya Adelaiye

“…This paper proposes a Hexadecimal Character Substitution Cipher (HCSC) algorithm aimed to reduce the computational resource utilization and reduce the size of the ciphertext after encryption thereby making the proposed algorithm suitable for deployment in mobile devices. …”
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Weed detection on embedded systems using computer vision algorithms by D. Shadrin, S. Illarionova, R. Kasatov, M. Akimenkova, G. Rudensky, E. Erhan

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Financial engineering and the digital economy: The implementations of machine learning algorithms by Pingping Fu, Honghao Yang, Wenhao Qian, ELsiddig Idriss Mohamed, Wafa Ali J. Almohri, Huda M. Alshanbari

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Machine learning algorithm for the rapid and accurate detection of Plasmodium falciparum by Mr Andrew Hill

“…Methods: Machine learning algorithms (MLA) consisting of a family of tiny (3,911 to 100,000 parameters) hybrid convolutional neural network / encoder-decoder models were developed which output a both a label {Parasite, Normal} and a confidence. …”
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A High-Performance and Lightweight Maritime Target Detection Algorithm by Shidan Sun, Zhiping Xu, Xiaochun Cao, Jiachun Zheng, Jiawen Yang, Ni Jin

“…To evaluate the performance of the proposed algorithm, the Singapore Maritime Dataset is adopted in our experiments. …”
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An Extended Analysis of the Correlation Extraction Algorithm in the Context of Linear Cryptanalysis by Christoph Graebnitz, Valentin Pickel, Holger Eble, Frank Morgner, Hannes Hattenbach, Marian Margraf

“…For this purpose, the Correlation Extraction Algorithm (CEA), which leverages the emerging field of quantum computing, appears promising. …”
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FPGA Implementations for Data Encryption and Decryption via Concurrent and Parallel Computation: A Review by Abdulmajeed Adil Yazdeen, Subhi R. M. Zeebaree, Mohammed Mohammed Sadeeq, Shakir Fattah Kak, Omar M. Ahmed, Rizgar R. Zebari

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Enjeux définitionnels et scientifiques de la littératie algorithmique : entre mécanologie et rétro-ingénierie documentaire by Olivier LE DEUFF, Rayya ROUMANOS

“…We then analyse the possible bridges that can be built with the many fields of social sciences that study algorithms and their effects. …”
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A Novel Scheme for Improving Accuracy of KNN Classification Algorithm Based on the New Weighting Technique and Stepwise Feature Selection by Saeid Sheikhi, Mohammad Taghi Kheirabadi, Amin Bazzazi

“…Though the KNN algorithm is highly effective in many cases, it has some essential deficiencies, which affects the classification accuracy of the algorithm. …”
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An Improved Global and Local Fusion Path-Planning Algorithm for Mobile Robots by Yongliang Shi, Shucheng Huang, Mingxing Li

“…However, existing state-of-the-art methods suffer from issues such as excessive path redundancy, too many turning points, and poor environmental adaptability. …”
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Application of Artificial Intelligence with Ant Colony Algorithm in construction projects schedule by Kiana Ahghari

“…Today, using project management methods and tools to realize the goals of many organizations and companiesIt is essential. …”
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A Solution Quality Assessment Method for Swarm Intelligence Optimization Algorithms by Zhaojun Zhang, Gai-Ge Wang, Kuansheng Zou, Jianhua Zhang

“…Therefore, there are still many problems to be solved. One problem is how to quantify the performance of algorithm in finite time, that is, how to evaluate the solution quality got by algorithm for practical problems. …”
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Systems and Algorithms for Wireless Sensor Networks Based on Animal and Natural Behavior by Sandra Sendra, Lorena Parra, Jaime Lloret, Shafiullah Khan

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