An Improved Virtual Terrain Generation Method Based On Simplex Noise,
2025
School of Surveying and Urban Spatial Information, Beijing University of Civil Engineering and Architecture, Beijing 102616, China
An Improved Virtual Terrain Generation Method Based On Simplex Noise, Bo Shen, Jianqin Zhang, Shuaibao Ma, Zheng Wen
Journal of System Simulation
Abstract: To address the issues of high computational complexity, slow generation speed, and insufficient realism present in traditional virtual terrain generation methods, this study proposed an improved virtual terrain generation method based on Simplex noise. This method leveraged the advantages of Simplex noise, such as high computational efficiency, low hardware overhead, and more natural randomness, to construct a basic terrain template. A fractal algorithm was introduced to enhance the level of terrain details through the superposition of noises with multiple frequencies and amplitudes. With the integration of a turbulence algorithm, random perturbations and complexity were added to further improve the …
Research On Constrained Programming Of Manipulator Using Rrt* Algorithm And Ellipse Prior,
2025
College of Intelligent Systems Science and Engineering, Harbin Engineering University, Harbin 150001, China
Research On Constrained Programming Of Manipulator Using Rrt* Algorithm And Ellipse Prior, Zhen Yang, Li Su, Zhiyu Cheng
Journal of System Simulation
Abstract: There are problems in the traditional RRT* algorithm using a uniform sampling strategy applied in constrained programming problems, such as inaccurate turning guidance of sampling points and unnecessary node cost comparisons, which lead to an increase in additional time costs. To address these issues, an improved RRT* algorithm was proposed. This algorithm leveraged a heuristic function cost of the projected sampling points to make an ellipse prior judgment on the sampling points. Based on the ellipse prior, the sampling points were judged to determine whether they could optimize the path and shorten the programming time. The geodesics were used …
Robust Identification Of Dual-Rate Sampled Nonlinear Systems Based On Salr Network,
2025
School of Internet of Things Engineering, Jiangnan University, Wuxi 214122, China
Robust Identification Of Dual-Rate Sampled Nonlinear Systems Based On Salr Network, Wenbin Jiang, Yuqing Cao, Li Xie, Huizhong Yang
Journal of System Simulation
Abstract: A robust identification algorithm based on the self-join adjacent-feedback loop reservoir (SALR) network was proposed for dual-rate sampled nonlinear systems with complex nonlinear characteristics and measurement outputs containing outliers. The SALR network was applied to describe the nonlinear characteristics of the target system, and wavelet neurons were injected into the reservoir to enhance its memory and nonlinear description capabilities. The identification problem of the nonlinear system was transformed into the identification problem of the network's output weight matrix. The Huber loss function was used to construct the criterion function, and an error threshold was introduced to improve the robustness …
Distributed Dispatch Method For Distribution Network And Microgrid Considering Diverse Regulating Resources,
2025
State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources (North China Electric Power University), Beijing 102206, China
Distributed Dispatch Method For Distribution Network And Microgrid Considering Diverse Regulating Resources, Yanbo Chen, Jiahao Yin, Tuben Qiang, Haoxin Tian, Yuxin Liang, Zhi Zhang
Journal of System Simulation
Abstract: Traditional centralized optimization-based dispatch methods for distribution networks struggle to balance the interests of multiple stakeholders while ensuring economic efficiency and operational reliability of the system. To address this issue, a distributed dispatch method for distribution network and microgrid considering diverse regulating resources was proposed. The operational models of the distribution network and microgrid were established by comprehensively incorporating active management elements and demand response mechanisms. A fuzzy chance-constrained method was employed to model the uncertainty in renewable energy output, thereby constructing a coordinated optimization dispatch model for distribution network and microgrid under renewable generation uncertainty. An improved goal …
Deep Learning Modeling Of Multi-Scale Characteristics Of Large-Scale Wind Turbine Gearbox,
2025
State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University, Beijing 102206, China; School of Control and Computer Engineering, North China Electric Power University, Beijing 102206, China
Deep Learning Modeling Of Multi-Scale Characteristics Of Large-Scale Wind Turbine Gearbox, Yang Hu, Zihao Li, Deyi Fu, Ziqiu Song, Fang Fang, Jizhen Liu
Journal of System Simulation
Abstract: To address challenges in characterizing high-frequency vibrations of wind turbine gearboxes, the long computation time of rigid-flexible coupled multi-body dynamics models, and the complexity of configuring gearbox models across multiple scenarios, this study proposed a deep learning modeling method for multi-scale operation using full-condition digital testing. The study proposed a cascaded extended simulation scheme based on stream data-driven OpenFAST and Adams and utilized dynamic mode decomposition technology to construct a multi-scale dataset for the flexible multi-body dynamics characteristics of the gearbox under all operating conditions of the wind turbine. Based on this dataset, a digital surrogate model covering multiple …
Optimization Dispatch Method For High-Proportion Renewable Energy Power Systems Based On Sc-Ppo,
2025
NR Electric Co. , Ltd. , Nanjing 211102, China
Optimization Dispatch Method For High-Proportion Renewable Energy Power Systems Based On Sc-Ppo, Zhongkai Xu, Chenyang Chu, Kai Xie, Ruizhuo Zhao, Wenjun Ke
Journal of System Simulation
Abstract: The high proportion of renewable energy integration brings significant challenges of randomness, multi-objective coupling, and security constraints to power systems. Traditional model-driven methods have limitations in modeling accuracy and adaptability. To address these issues, this paper proposed a safety-constrained PPO algorithm (SC-PPO). The method included three improvements. A temporal convolutional network was utilized to construct a dynamic state encoder that integrated historical operation, real-time monitoring, and prediction data to form a causal state representation. A hierarchical reward structure was designed, and an adaptive weighting mechanism based on constraint satisfaction degree was introduced to coordinate multi-objective optimization. Physical constraint projection …
Microsimulation Of Infectious Disease Transmission Considering Virus Release, Transmission, And Action,
2025
Business School, University of Shanghai for Science & Technology, Shanghai 200093, China; School of Intelligent Emergency Management, University of Shanghai for Science & Technology, Shanghai 200093, China
Microsimulation Of Infectious Disease Transmission Considering Virus Release, Transmission, And Action, Zhiming Fang, Shengdong Yuan, Ge Huang, Jingqian Yang, Zhongyi Huang
Journal of System Simulation
Abstract: Existing infection risk assessment methods mostly evaluate infection probability through mathematical models or simulation, but they lack analysis of the relationship between air circulation and individual infection probability. This study proposed a risk prediction model for infectious disease transmission based on indoor air circulation. At the microscopic scale, the space was discretized into grid points. By integrating CFD numerical simulation, the entire process of virus droplet release, transmission, and action was fully simulated. The simulation results show that in an obstacle-free room, the error between the total indoor viral load predicted by the model under windless and low wind …
Path Planning For Mobile Robots Based On Improved Rrt-Connect And Dwa Fusion,
2025
School of Control and Computer Engineering, North China Electric Power University, Beijing 102206, China
Path Planning For Mobile Robots Based On Improved Rrt-Connect And Dwa Fusion, Yi Luo, Jia Deng
Journal of System Simulation
Abstract: To improve the efficiency and quality of dynamic path planning for mobile robots in complex environments, this paper proposed a path planning algorithm that combined an improved RRT-connect with the DWA. Two expanding random trees were introduced for alternating expansion, and a dynamically restricted sampling area was set to reduce the randomness of the sampling process while ensuring the probability completeness of the algorithm. A target bias adaptive step size strategy was employed to enhance the target orientation of the random tree expansion process. A greedy strategy was adopted to prune redundant nodes in the path and smooth the …
Modeling And Simulation Of Traffic Signal Control Based On Mlp With Improved Gcn-Td3,
2025
School of Electrical Engineering, Xinjiang University, Urumqi 830017, China
Modeling And Simulation Of Traffic Signal Control Based On Mlp With Improved Gcn-Td3, Deqi Huang, Yating Tu, Zhenhua Zhang, Xin Guo
Journal of System Simulation
Abstract: To address the issues of uneven traffic flow at urban intersections, limited road capacity, and the poor coordination of existing traffic signal control algorithms, a traffic signal control algorithm based on graph convolutional reinforcement learning was proposed. By utilizing a multilayer perceptron, the dynamic features of vehicles and phase information at the controlled intersection and its neighboring intersections were extracted. A graph convolutional neural network was then employed to aggregate these vehicle dynamic features into potential features representing regional traffic. The control strategy was derived through multiple iterations of an improved twin delayed deep deterministic policy gradient (TD3) algorithm. …
Dynamic Order Scheduling For Pick-And-Pass System Considering Workload Balance And Learning Effects,
2025
Sino-US Global Logistics Institute, Antai College of Economics & Management, Shanghai Jiao Tong University, Shanghai 200030, China
Dynamic Order Scheduling For Pick-And-Pass System Considering Workload Balance And Learning Effects, Weihong Liu, Sixiang Zhao, Dali Zhang, Zhenhui Jiang
Journal of System Simulation
Abstract: In e-commerce logistics, the hybrid pick-and-pass systems offer both complexity and flexibility, enabling adaptation to a wider range of order picking scenarios. Therefore, they have been widely used. However, this also complicates the order scheduling problem, particularly when both workload balance and pickers' learning effects need to be considered. Efficiently scheduling orders to reduce picking time under these conditions poses a significant challenge. This study began by constructing a mathematical model for the static scheduling problem with known orders. Based on this model, a simulation model of hybrid pick-and-pass zones was developed, and a scheduling rule incorporating multiple system …
Simulation And Optimization Of Continuous Motion Control Based On Spiking Reinforcement Learning,
2025
Intelligent Science & Technology Academy of CASIC, Beijing 100043, China
Simulation And Optimization Of Continuous Motion Control Based On Spiking Reinforcement Learning, Xiaode Liu, Yufei Guo, Yuanpei Chen, Jie Zhou, Yuhan Zhang, Weihang Peng, Zhe Ma
Journal of System Simulation
Abstract: To improve the model robustness for multi-degree-of-freedom continuous motion control, an intelligent motion control algorithm was proposed based on the Actor-Critic reinforcement learning framework and spiking neural networks. This algorithm integrateed the Actor network with spiking population coding and enhanced model training performance by introducing feature transformation methods. The Critic network was used to evaluate the effectiveness of the motion control. The results show that, compared to other reinforcement learning algorithms, the average reward value of this method increases by more than 10%. The simulation results validate the effectiveness of the model in improving multi-degree-of-freedom continuous control performance.
Distributed Heterogeneous Hybrid Flow-Shop Scheduling Considering Combined Buffer,
2025
School of Management, Zhengzhou University, Zhengzhou 450001, China
Distributed Heterogeneous Hybrid Flow-Shop Scheduling Considering Combined Buffer, Hua Xuan, Lin Lü, Bing Li
Journal of System Simulation
Abstract: In order to reduce cost losses caused by delivery delays, distributed heterogeneous hybrid flowshop scheduling problems under combined buffer conditions of finite buffer and zero-wait were studied. A hybrid estimation of distribution algorithm based on Q-learning was proposed to minimize total weighted earliness and tardiness. For the combined buffer, dynamic decoding was designed based on the average factory allocation strategy and the shortest path method. The initial job group was optimized by reverse learning. Q-learning was embedded in the probabilistic model for intelligent searching and updating based on the group state. Reconstruction of the job group was completed using …
Tacscope: A Miniaturized Vision-Based Tactile Sensor For Surgical Applications,
2025
Purdue University
Tacscope: A Miniaturized Vision-Based Tactile Sensor For Surgical Applications, Md Rakibul Islam Prince, Sheeraz Athar, Pokuang Zhou, Yu She
School of Industrial Engineering Faculty Publications
The lack of tactile feedback in robot-assisted minimally invasive surgery (RMIS) limits surgeons’ ability to palpate tissues, a critical technique for locating abnormalities such as tumors. To address this challenge, we introduce TacScope, a novel, vision-based tactile sensor leveraging the magnification properties of a spherical-surface elastomer to provide tactile feedback for advanced clinical applications. TacScope features a robust, low-cost, and easyly fabricate design, enabling seamless integration into surgical robotic setups. It reconstructs high-resolution 3D geometry from variations in particle-density distribution across its elastomer surface, requiring only a single image for calibration. The curved elastomer membrane alters particle-density distribution under …
Condition Optimization For The Synthesis Of Castor Oil Templated Mesoporous Silica,
2025
Department of Chemistry, Faculty of Science, Mkwawa University College of Education, University of Dar es Salaam, P.O. Box 2513, Iringa, Tanzania
Condition Optimization For The Synthesis Of Castor Oil Templated Mesoporous Silica, Godlisten Namwel Shao
Tanzania Journal of Engineering and Technology (TJET)
The present work provides suitable conditions for the synthesis of mesoporous materials with improved porosity using an optimization technique. The proposed preparation method involves forming final products by varying the amount of castor oil, media, and template removal. The obtained samples were examined by TGA, XRD, DRIFT and nitrogen physisorption studies. It was observed that the porosity of the obtained samples was dependent on the conditions under which the materials were synthesized. All synthesized materials showed the Type IV adsorption-desorption isotherm features of mesoporous, regardless of the conditions utilized during the synthesis. The sample synthesized using 2.5 g of a …
Adoption Of Agrivoltaics In Developing Countries: A Review On Challenges, Opportunities And Future Prospects,
2025
Department of Electrical Engineering, University of Dar es Salaam, P.O. Box 33335, Dar es Salaam, Tanzania
Adoption Of Agrivoltaics In Developing Countries: A Review On Challenges, Opportunities And Future Prospects, Abdi J. Athumani, Pater Makolo
Tanzania Journal of Engineering and Technology (TJET)
This paper provides a review of agrivoltaics technology and how it has been applicable in developing countries, including African countries. Agrivoltaics, the integration of agricultural production with photovoltaic energy generation, offers promising solutions to water- energy-food nexus in developing countries. This technology offers the dual benefit of increasing agricultural productivity while generating clean energy, which is very important for regions facing frequent electricity shortages and declining agricultural yields due to climate change. However, despite its potential, the adoption of agrivoltaics in developing nations remains limited in comparison to developed countries due to financial, technical and policy constraints. This paper explores …
Cnn-Based Hybrid Model For Detecting Blight Diseases In Potato Crops With Advanced Image Processing Techniques,
2025
Department of Informatics and Information Technology, College of Natural and Applied Sciences, Sokoine University of Agriculture, P.O. Box 3000, Morogoro, Tanzania
Cnn-Based Hybrid Model For Detecting Blight Diseases In Potato Crops With Advanced Image Processing Techniques, Farian S. Ishengoma
Tanzania Journal of Engineering and Technology (TJET)
Potato production plays a vital role in global agriculture as a major food source for large populations. However, potato crops are highly susceptible to diseases, particularly Early Blight and Late Blight, which result in substantial yield losses. Timely detection and effective control of these diseases are essential for maintaining stable crop output. This study explores the integration of Convolutional Neural Networks (CNNs) and advanced image processing techniques to differentiate between diseased and healthy potato plants accurately. Two datasets comprising original and enhanced images were used to train four CNN models: InceptionV3, Xception, Densenet201, and Resnet152V2. The original images underwent background …
Multi-Material Printer Development,
2025
California Polytechnic State University, San Luis Obispo
Multi-Material Printer Development, Jessica Hu, Phoebe Eplett
College of Engineering Summer Undergraduate Research Program
Surgeons require pre-surgical models to practice procedures and improve success rates. However, the current process of creating physical models for practice using 3D printing is limited to producing homogeneous mimics of the human body, while the human body is a heterogeneous structure composed of multiple materials with varying properties, including bones, muscles, and skin. Additive manufacturing methods cannot easily print multiple materials simultaneously, as current AM machines only print homogeneous material, unlike the human body. In this proposal, we aim to develop a multi-material additive manufacturing system, from software to hardware, to manufacture pre-surgical models. We will investigate multi-material AM …
Evaluating The Accuracy Of Gen Ai Detecting Misinformation,
2025
California Polytechnic State University, San Luis Obispo
Evaluating The Accuracy Of Gen Ai Detecting Misinformation, Alan Sebastian
College of Engineering Summer Undergraduate Research Program
This research project will investigate the ability of advanced Large Language Models (LLMs) to identify and assess misinformation across diverse forms of media, including text, images, and video. In an age where misleading content spreads rapidly across digital platforms, evaluating the reliability and integrity of AI systems tasked with fact-checking is critical. We will develop a comprehensive dataset composed of factual and misleading examples drawn from various well-known and reliable fact-checking organizations. Each item will be independently reviewed and transparently labeled to ensure reproducibility. We will then prompt a curated group of state-of-the-art LLMs—including GPT-4, Claude, Gemini, Perplexity, Grok, and …
3d Printing Scoliosis Braces,
2025
California Polytechnic State University, San Luis Obispo
3d Printing Scoliosis Braces, Zak Neddo, Jaylan Mo
College of Engineering Summer Undergraduate Research Program
As 3D printing technology continues to transform the healthcare industry, the need for FDA-compliant additive manufacturing facilities in public universities has become increasingly important. While private companies and medical research institutions have successfully integrated 3D printing for medical device prototyping and surgical planning, public universities—including Cal Poly—lack the dedicated infrastructure needed to support FDA-regulated medical manufacturing and research. This project aims to bridge that gap by researching, designing, and implementing a dedicated FDA-compliant section within Cal Poly’s multi-purpose 3D Printing Facility. Over the course of eight weeks, student researchers will study FDA regulations, design an optimized facility layout, and implement …
Deepseek, Chatgpt, Or Gemini? A Multi-Method Investigation Of Neural And Behavioral User Experience (Ux),
2025
California Polytechnic State University, San Luis Obispo
Deepseek, Chatgpt, Or Gemini? A Multi-Method Investigation Of Neural And Behavioral User Experience (Ux), Keziah Gopalla
College of Engineering Summer Undergraduate Research Program
As artificial intelligence tools become integral to everyday tasks, understanding how users interact with these systems is essential for improving user experience and system design. This research aims to investigate and compare the interface usability and emotional responses elicited by three prominent AI tools—ChatGPT, DeepSeek, and Google Gemini—using the Emotiv Insight EEG headset. By combining usability testing with emotional biometrics, this study offers a novel approach to evaluating conversational AI systems. The study will capture both subjective usability metrics and objective emotional markers such as arousal, valence, and engagement. Participants will complete standardized tasks using each AI tool, while their …
