Chimp Optimization Algorithm(ChOA)is one of the recent metaheuristics swarm intelligence *** has been widely tailored for a wide variety of optimization problems due to its impressive characteristics over other swarm ...
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Chimp Optimization Algorithm(ChOA)is one of the recent metaheuristics swarm intelligence *** has been widely tailored for a wide variety of optimization problems due to its impressive characteristics over other swarm intelligence methods:it has very few parameters,and no derivation information is required in the initial ***,it is simple,easy to use,flexible,scalable,and has a special capability to strike the right balance between exploration and exploitation during the search which leads to favorable ***,the ChOA has recently gained a very big research interest with tremendous audiences from several domains in a very short ***,in this review paper,several research publications using ChOA have been overviewed and ***,introductory information about ChOA is provided which illustrates the natural foundation context and its related optimization conceptual *** main operations of ChOA are procedurally discussed,and the theoretical foundation is ***,the recent versions of ChOA are discussed in detail which are categorized into modified,hybridized,and paralleled *** main applications of ChOA are also thoroughly *** applications belong to the domains of economics,image processing,engineering,neural network,power and energy,networks,*** of ChOA is also *** review paper will be helpful for the researchers and practitioners of ChOA belonging to a wide range of audiences from the domains of optimization,engineering,medical,data mining,and *** well,it is wealthy in research on health,environment,and public ***,it will aid those who are interested by providing them with potential future research.
Unmanned aerial vehicles (UAVs) have garnered significant attention from the research community during the last decade, due to their diverse capabilities and potential applications. One of the most critical functions ...
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ISBN:
(数字)9798350368833
ISBN:
(纸本)9798350368840
Unmanned aerial vehicles (UAVs) have garnered significant attention from the research community during the last decade, due to their diverse capabilities and potential applications. One of the most critical functions that drones must execute efficiently is navigation in real-world environments. This paper presents a decentralized approach for enabling unmanned aerial vehicles (UAVs) to navigate safely in unknown environments and avoid obstacles. Leveraging the Optimal Reciprocal Collision Avoidance (ORCA) algorithm, implemented in the Robot Operating System (ROS), our method facilitates conflict detection and resolution in 2D environments. Through simulations using ROS, Gazebo, and Iris drones, we validate the effectiveness of our approach in scenarios with initial trajectory conflicts. Our work addresses the pressing need for UAVs to autonomously plan and execute safe flights, laying the groundwork for enhanced UAV capabilities in various real-world applications. The simulation results demonstrate the efficiency and robustness of our approach.
This paper examines the reproducibility of massive information analytics under particular factors. The paper proposes the 'performing Scalable Inference' technique to cope with scalability troubles and to expl...
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Autonomous Underwater Gliders (AUGs) are extensively developed vehicles capable of prolonged exploration and observation in complex marine environments. Control of the AUG is challenging due to its slow response syste...
Autonomous Underwater Gliders (AUGs) are extensively developed vehicles capable of prolonged exploration and observation in complex marine environments. Control of the AUG is challenging due to its slow response system and its constraints. In this research, a linear model representation of AutoRegressive eXogenous input (ARX) will be constructed using input and output data from the AUG system, built Model Predictive Control (MPC), analyzed the performance, comparing with traditional Proportional-Integral-Derivative (PID). The objective is to enhance setpoint tracking accuracy and minimize energy to extend exploration time while faced with constraints. Simulation results reveal MPC exhibits potential setpoint tracking, low overshoot as low as 0.6% up to 0.3m/s maximum depth rate, has relatively low input changes indicating good efficiency compared to PID. MPC approach effectively addresses slow response systems, managing momentum, and handling actuator constraints commonly encountered in AUG.
The process of continuous steel casting, specifically the part of secondary cooling, is a typical representative of a system with distributed parameters. The paper deal with the synthesis and simulation of robust cont...
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ISBN:
(数字)9781665466363
ISBN:
(纸本)9781665466370
The process of continuous steel casting, specifically the part of secondary cooling, is a typical representative of a system with distributed parameters. The paper deal with the synthesis and simulation of robust control of continuous steel casting in the secondary cooling zone. During steel production, there is a smooth change between the types of steel produced (or steel grades), to which the control system must react flexibly. Therefore, a robust approach based on simple PID controllers will be chosen for control synthesis. Based on the model obtained from the ProCast software, the uncertainty limits for the simulation model will be determined. Robust control simulations will be performed on a time-space circuit, within the simulations a possible machine failure will be tested, thus a change in cooling power in individual zones. The results will be presented as temperature fields, representing the system with distributed parameters, taking into account the time and space distribution of the controlled temerature.
This paper presents the development of a multilingual hate speech detection model that effectively processes and classifies content in both Arabic and English. The study leverages both traditional machine learning mod...
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Named Data Networking as an alternative network for 5G network traffic is required to be able to provide better performance compared to other networks such as internet protocol networks. In NDN wireless, it is known t...
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ISBN:
(数字)9798350377057
ISBN:
(纸本)9798350377064
Named Data Networking as an alternative network for 5G network traffic is required to be able to provide better performance compared to other networks such as internet protocol networks. In NDN wireless, it is known that there is producer mobility and consumer mobility, so optimal mobility management is needed, including the handover process. In this paper the author proposes a simple RSSI-based 5G handover algorithm with distance as a reference RSSI value. This algorithm is a preparation for the handover algorithm on the NDN wireless network. By using the assumed distance value MS to eNB as the basic value for calculating RSSI, handover determination is determined by comparing the RSSI value to the RSSI threshold value. With the scenario of different numbers of users and cluster sizes, from the handover process involving 8 eNB. It can be calculated how big the handover probability is for each user. From the simulation results, it can be concluded that the more users and the larger the cluster size, the greater the handover probability value. This is linear, with the wider the cluster, the probability of getting an RSSI signal from the original eNB becomes smaller, making it possible to get an RSSI signal from neighboring eNB, so that a handover occurs.
Organisations and users have been experiencing significant rises in cyberattacks and their severity, which means that they require a greater awareness and understanding of the anatomy of cyberattacks, to prevent and m...
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Cardiovascular diseases, also known as CVDs, currently rank as the primary incidence of mortality. The present approach for identifying illnesses involves the analysis of the Electrocardiogram (ECG), an electronic dia...
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作者：
Aleksandr BeznosikovSamuel HorváthPeter RichtárikMher SafaryanComputer
Electrical and Math. Sciences and Engineering Division King Abdullah University of Science and Technology Thuwal KSA and Skolkovo Institute of Science and Technology Moscow Russia and School of Applied Mathematics and Informatics Moscow Institute of Physics and Technology Moscow Russia Computer
Electrical and Math. Sciences and Engineering Division King Abdullah University of Science and Technology Thuwal KSA
In the last few years, various communication compression techniques have emerged as an indispensable tool helping to alleviate the communication bottleneck in distributed learning. However, despite the fact biased com...
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In the last few years, various communication compression techniques have emerged as an indispensable tool helping to alleviate the communication bottleneck in distributed learning. However, despite the fact biased compressors often show superior performance in practice when compared to the much more studied and understood unbiased compressors, very little is known about them. In this work we study three classes of biased compression operators, two of which are new, and their performance when applied to (stochastic) gradient descent and distributed (stochastic) gradient descent. We show for the first time that biased compressors can lead to linear convergence rates both in the single node and distributed settings. We prove that distributed compressed SGD method, employed with error feedback mechanism, enjoys the ergodic rate $O\left( \delta L \exp[-\frac{\mu K}{\delta L}] + \frac{(C + \delta D)}{K\mu}\right)$, where δ ≥1 is a compression parameter which grows when more compression is applied, L and µ are the smoothness and strong convexity constants, C captures stochastic gradient noise (C = 0 if full gradients are computed on each node) and D captures the variance of the gradients at the optimum (D = 0 for over-parameterized models). Further, via a theoretical study of several synthetic and empirical distributions of communicated gradients, we shed light on why and by how much biased compressors outperform their unbiased variants. Finally, we propose several new biased compressors with promising theoretical guarantees and practical performance.
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