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Enhancing Wireless Sensor Network Efficiency through Al-Biruni Earth Radius Optimization

Computers, Materials & Continua 2024年第6期79卷 3549-3568页

作者： Reem Ibrahim Alkanhel Doaa Sami Khafaga Ahmed Mohamed Zaki Marwa M.Eid Abdyalaziz A.Al-Mooneam Abdelhameed Ibrahim S.K.Towfek Department of information Technology College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Computer Science and intelligent Systems Research Center BlacksburgVirginia24060USA Delta Higher Institute for engineering and Technology Mansoura35511Egypt Faculty of Artificial Intelligence Delta University for Science and TechnologyMansoura35712Egypt Artificial Intelligence and Computational Intelligence Research Center MeridenConnecticut06450USA School of ICT Faculty of EngineeringDesign and Information&Communications Technology(EDICT)Bahrain PolytechnicP.O.Box 33349Isa TownBahrain

The networks of wireless sensors provide the ground for a range of applications,including environmental moni-toring and industrial *** the networks can overcome obstacles like power and communication reliability and sensor coverage is the crux of network *** infrastructure planning should be focused on increasing performance,and it should be affected by the detailed data about node *** work recommends the creation of each sensor’s specs and radius of influence based on a particular geographical location,which will contribute to better network planning and *** using the ARIMA model for time series forecasting and the Al-Biruni Earth Radius algorithm for optimization,our approach bridges the gap between successive terrains while seeking the equilibrium between exploration and *** implementing adaptive protocols according to varying environments and sensor constraints,our study aspires to improve overall network *** compare the Al-Biruni Earth Radius algorithm along with Gray Wolf Optimization,Particle Swarm Optimization,Genetic Algorithms,and Whale Optimization about performance on real-world *** the most efficient in the optimization process,Biruni displays the lowest error rate at *** two other statistical techniques,like ANOVA,are also useful in discovering the factors influencing the nature of sensor data and network-specific *** to the multi-faceted support the comprehensive approach promotes,there is a chance to understand the dynamics that affect the optimization outcomes better so decisions about network design can be *** delivering better performance and reliability for various in-situ applications,this research leads to a fusion of time series forecasters and a customized optimizer algorithm.

关键词： Wireless sensor networks optimization ARIMA model BER algorithm metaheuristic algorithms

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Tjong:A transformer‐based Mahjong AI via hierarchical decision‐making and fan backward

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CAAI Transactions on Intelligence Technology 2024年第4期9卷 982-995页

作者： Xiali Li Bo Liu Zhi Wei Zhaoqi Wang Licheng Wu School of information and engineering Minzu University of ChinaBeijingChina Key Laboratory of Ethnic Language intelligent Analysis and Security Governance of MOE Minzu University of ChinaBeijingChina Department of Computer Science New Jersey Institute of TechnologyNewarkNew JerseyUSA

Mahjong,a complex game with hidden information and sparse rewards,poses significant *** Mahjong AIs require substantial hardware resources and extensive datasets to enhance AI *** authors propose a transformer‐based Mahjong AI(Tjong)via hierarchical decision‐*** utilising self‐attention mechanisms,Tjong effectively captures tile patterns and game dynamics,and it decouples the decision pro-cess into two distinct stages:action decision and tile *** design reduces de-cision complexity ***,a fan backward technique is proposed to address the sparse rewards by allocating reversed rewards for actions based on winning *** consists of 15M parameters and is trained using approximately 0.5 M data over 7 days of supervised learning on a single server with 2 *** action decision achieved an accuracy of 94.63%,while the claim decision attained 98.55%and the discard decision reached 81.51%.In a tournament format,Tjong outperformed AIs(CNN,MLP,RNN,ResNet,VIT),achieving scores up to 230%higher than its ***-more,after 3 days of reinforcement learning training,it ranked within the top 1%on the leaderboard on the Botzone platform.

关键词： decision making deep learning deep neural networks

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Dynamic Hypergraph Modeling and Robustness Analysis for SIoT

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Computer Modeling in engineering & sciences 2024年第9期140卷 3017-3034页

作者： Yue Wan Nan Jiang Ziyu Liu School of information engineering East China Jiaotong UniversityNanchang330013China

The Social Internet of Things(SIoT)integrates the Internet of Things(IoT)and social networks,taking into account the social attributes of objects and diversifying the relationship between humans and objects,which overcomes the limitations of the IoT’s focus on associations between *** Intelligence(AI)technology is rapidly *** is critical to build trustworthy and transparent systems,especially with system security issues coming to the *** paper emphasizes the social attributes of objects and uses hypergraphs to model the diverse entities and relationships in SIoT,aiming to build an SIoT hypergraph generation model to explore the complex interactions between entities in the context of intelligent *** hypergraph generation models impose too many constraints and fail to capture more details of real *** contrast,this paper proposes a hypergraph generation model that evolves dynamically over time,where only the number of nodes is *** combines node wandering with a forest fire model and uses two different methods to control the size of the *** new nodes are added,the model can promptly reflect changes in entities and relationships within *** results exhibit that our model can effectively replicate the topological structure of real-world *** also evaluate the vulnerability of the hypergraph under different attack strategies,which provides theoretical support for building a more robust intelligent SIoT hypergraph model and lays the foundation for building safer and more reliable systems in the future.

关键词： Large-scale artificial intelligence Social Internet of Things hypernetwork robustness analysis

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A Novel Predictive Model for Edge Computing Resource Scheduling Based on Deep Neural Network

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Computer Modeling in engineering & sciences 2024年第4期139卷 259-277页

作者： Ming Gao Weiwei Cai Yizhang Jiang Wenjun Hu Jian Yao Pengjiang Qian School of Artificial Intelligence and Computer Science Jiangnan UniversityWuxi214122China The Center for intelligent Systems and Applications Research School of Artificial Intelligence and Computer ScienceJiangnan UniversityWuxi214122China School of information engineering Huzhou UniversityHuzhou313000China

Currently,applications accessing remote computing resources through cloud data centers is the main mode of operation,but this mode of operation greatly increases communication latency and reduces overall quality of service(QoS)and quality of experience(QoE).Edge computing technology extends cloud service functionality to the edge of the mobile network,closer to the task execution end,and can effectivelymitigate the communication latency ***,the massive and heterogeneous nature of servers in edge computing systems brings new challenges to task scheduling and resource management,and the booming development of artificial neural networks provides us withmore powerfulmethods to alleviate this ***,in this paper,we proposed a time series forecasting model incorporating Conv1D,LSTM and GRU for edge computing device resource scheduling,trained and tested the forecasting model using a small self-built dataset,and achieved competitive experimental results.

关键词： Edge computing resource scheduling predictive models

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Segment-wise learning control for trajectory tracking of robot manipulators under iteration-dependent periods

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Science China(information sciences) 2024年第3期67卷 155-166页

作者： Fan ZHANG Deyuan MENG Kaiquan CAI The Seventh Research Division Beihang University School of Automation Science and Electrical engineering Beihang University School of Electronics and information engineering Beihang University

This paper is concerned with the amplitude boundedness problem of adaptive iterative learning control(AILC) for robot manipulators operating with iteration-dependent periods. By introducing virtual memory slots for storing historical data, a practical AILC method is proposed to achieve the segmentwise learning. This method requires less memory storage for historical information of previous iterations,especially in comparison with that of the conventional AILC methods using point-wise learning *** is shown that not only the energy boundedness but also the amplitude boundedness of estimates and inputs of practical AILC can be guaranteed. Moreover, the practical AILC method can achieve the perfect tracking objective regardless of iteration-dependent periods when the robot manipulators have a persistent full learning property. In addition, a solution to the visual manipulator platform is provided and deployed based on Coppeliasim and Matlab, which helps to show the amplitude boundedness of learning results and the perfect tracking performances of the proposed practical AILC method for robot manipulators.

关键词： amplitude boundedness iteration-dependent period iterative learning control robot manipulator segment-wise virtual memory slot

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Traffic Flow Prediction with Heterogeneous Spatiotemporal Data Based on a Hybrid Deep Learning Model Using Attention-Mechanism

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Computer Modeling in engineering & sciences 2024年第8期140卷 1711-1728页

作者： Jing-Doo Wang Chayadi Oktomy Noto Susanto Departement of Computer Science and information engineering Asia UniversityTaichungTaiwanChina Departement of information Technology Universitas Muhammadiyah YogyakartaYogyakartaIndonesia

A significant obstacle in intelligent transportation systems(ITS)is the capacity to predict traffic *** advancements in deep neural networks have enabled the development of models to represent traffic flow ***,accurately predicting traffic flow at the individual road level is extremely difficult due to the complex interplay of spatial and temporal *** paper proposes a technique for predicting short-term traffic flow data using an architecture that utilizes convolutional bidirectional long short-term memory(Conv-BiLSTM)with attention *** studies neglected to include data pertaining to factors such as holidays,weather conditions,and vehicle types,which are interconnected and significantly impact the accuracy of forecast *** addition,this research incorporates recurring monthly periodic pattern data that significantly enhances the accuracy of forecast *** experimental findings demonstrate a performance improvement of 21.68%when incorporating the vehicle type feature.

关键词： Traffic flow prediction sptiotemporal data heterogeneous data Conv-BiLSTM data-centric intra-data

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Anti-Jamming Null Space Projection Beamforming Based on Symbiotic Radio

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工程与科学中的计算机建模(英文) 2024年第1期138卷 679-689页

作者： Baofeng Ji Yifan Liu Tingpeng Li Ling Xing Weixing Wang Shahid Mumtaz Xiaolong Shang Wanying Liu Congzheng Han State Key Laboratory of Complex Electromagnetic Environment Effects on Electronics and information System(CEMEE) Luoyang471000China Research and Innovation Center of intelligent System Longmen LaboratoryLuoyang471000China College of information engineering Henan University of Science and TechnologyLuoyang471000China Institute of Atmospheric Physics Chinese Academy of Sciences(LAGEO)Beijing100000China Instituto de Telecomunicaes Aveiro3800-005Portugal Chinese Academy of Agricultural Mechanization sciences Beijing100000China

With the development of information technology,more and more devices are connected to the Internet through wireless communication to complete data *** to the broadcast characteristics ofwireless channels,wireless networks have suffered more and more malicious *** layer security has received extensive attention from industry and *** is considered to be one of the most important technologies related to physical layer *** beamforming technology,messages can be transmitted to legitimate users in an offset direction that is as orthogonal as possible to the interference channel to ensure the reception SINR by legitimate *** the symbiotic radio(SR)technology,this paper considers a symbiotic radio antijamming MIMO system equipped with a multi-antenna system at the main base *** order to avoid the interference signal and improve the SINR of the signal received by the *** base station is equipped with a uniform rectangular antenna array,and using Null Space Projection(NSP)Beamforming,intelligent Reflecting Surface(IRS)can assist in changing the beam’s *** simulation results show that NSP Beamforming could make a better use of the null space of interference,which can effectively improve the received SINR of users under directional interference,and improve the utilization efficiency of signal energy.

关键词： Symbiotic radio anti-jamming MIMO NSP Beamforming physical layer security

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Integrating sequence and graph information for enhanced drug-target affinity prediction

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Science China(information sciences) 2024年第2期67卷 325-326页

作者： Haohuai HE Guanxing CHEN Calvin Yu-Chian CHEN Artificial Intelligence Medical Research Center School of Intelligent Systems EngineeringShenzhen Campus of Sun Yat-sen University

Drug discovery is a pivotal discipline involving the identification and development of innovative pharmaceuticals designed to combat a wide array of illnesses. It plays a crucial role in advancing global health outcomes and improving the standard of living for individuals worldwide. However,drug discovery often relies on laborious in vitro experiments,

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Research and application of composite stochastic resonance in enhancement detection

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Chinese Physics B 2024年第1期33卷 264-273页

作者：高蕊焦尚彬薛琼婕 School of Automation and information engineering Xi'an University of TechnologyXi'an 710048China School of Electronic and Electrical engineering Baoji University of Arts and SciencesBaoji 721016China Shaanxi Key Laboratory of Complex System Control and intelligent information Processing Xi'an University of TechnologyXi'an 710048China

Aiming at the problem that the intermediate potential part of the traditional bistable stochastic resonance model cannot be adjusted independently, a new composite stochastic resonance(NCSR) model is proposed by combining the Woods–Saxon(WS) model and the improved piecewise bistable model. The model retains the characteristics of the independent parameters of WS model and the improved piecewise model has no output saturation, all the parameters in the new model have no coupling characteristics. Under α stable noise environment, the new model is used to detect periodic signal and aperiodic signal, the detection results indicate that the new model has higher noise utilization and better detection ***, the new model is applied to image denoising, the results showed that under the same conditions, the output peak signal-to-noise ratio(PSNR) and the correlation number of NCSR method is higher than that of other commonly used linear denoising methods and improved piecewise SR methods, the effectiveness of the new model is verified.

关键词： Woods–Saxon improved piecewise model composite stochastic resonance(SR) image denoising

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Policy iteration-based adaptive optimal control for Markov jump systems: a transition-probability-free asynchronous approach

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Science China(information sciences) 2024年第11期67卷 363-364页

作者： Weidi CHENG Chengcheng REN Shuping HE Changyin SUN Key Laboratory of intelligent Computing and Signal Processing (Ministry of Education) School of Electrical Engineering and Automation Anhui University Anhui engineering Laboratory of Human-Robot Integration System and intelligent Equipment School of Electrical Engineering and Automation Anhui University information Materials and intelligent Sensing Laboratory of Anhui Province engineering Research Center of Autonomous Unmanned System Technology (Ministry of Education) School of Artificial Intelligence Anhui University

The controller and filter design problems of Markov jump systems(MJSs) have gained significant attention over the past few decades. These studies include various aspects,including stochastic stabilization [1], optimal tracking control [2], and dissipative filter design [3]. Although numerous publications address the optimal controller design for MJSs, the issue of hidden MJSs, particularly those with mismatched jumping modes between the system and the controller, has rarely been explored.

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