Computer Engineering Commons^™

Decision Modeling And Solution Based On Game Adversarial Complex Systems, Jiachen Jiang, Zhengxuan Jia, Zhao Xu, Tingyu Lin, Pengpeng Zhao, Yiming Ou

Journal of System Simulation

Abstract: In view of the complex situation of the current game which will be large-scale, high-intensity, not omniscient, and strong confrontation, and in response to the lack of flexibility and long iteration cycles in traditional game decision-making, the model of the unmanned complex game system is built according to the background of the unmanned red and blue game. Based on deep reinforcement learning technology, intelligent decision-making algorithms are studied in the background of unmanned red and blue games. With the help of deep neural networks and Bellman's optimal principle, the search of the huge solution space is more efficient, and …

Cooperative Control Method Of Mixed Traffic At Signalized Intersection, Qiushi Huang, Yanyang Wang, Changliang Wu, Junfu Huang, Shenggen Zhang, Haoxuan Luo

Journal of System Simulation

Abstract: A hierarchical decoupling cooperative control method for signal light mixed traffic platoon is designed with the goal of improving the traffic environment at signalized intersections. In the research of upper layer signal control, a calculation model for vehicle delay time at intersections is selected, with the goal of minimizing the average delay time of vehicles. A genetic algorithm based upper layer control strategy for intersection signal lights is proposed and verified; in the research of lower layer mixed platoon control, a "1+N" form is used to establish a dynamic model of the mixed platoon. A vehicle energy consumption model …

Driverless Vehicles Distribution Problem In Communities In Cooperation Of Storage Points, Xiaolong Diao

Journal of System Simulation

Abstract: With the development of smart communities, the distribution of driverless vehicles in communities has become a focus of government, operators and researchers. The joint cooperation of storage points in communities is designed to balance the the distribution of each storage point and avoid the high input cost of driverless vehicles, which means that driverless vehicles can travel between different storage points. The driverless vehicle distribution problem proposed in this paper includes the unloading subproblem and the driverless vehicle scheduling subproblem. For the unloading subproblem, the unloading scheme of vehicles at storage points is optimized with the aim of minimizing …

Multi-Uav Deployment And Collaborative Offloading For Large-Scale Iot Systems, Zhiqin Huang, Tianying Lu, Zheyi Chen

Journal of System Simulation

Abstract: In large-scale internet-of-things (IoT) systems, unmanned aerial vehicles (UAV) enabled mobile edge computing (MEC) can alleviate the performance constraints on end IoT devices. However, due to the uneven distribution of IoT devices and inefficient problem-solving, how to efficiently perform computation offloading in large-scale IoT systems is a major challenge. Existing solutions generally cannot fit into dynamic multi-UAV scenarios, causing inefficient resource utilization and excessive response delay. To address these important challenges, this paper proposes a novel multi-UAV deployment and collaborative offloading (MUCO) method for large-scale IoT systems. A UAV deployment scheme based on constrained K-Means clustering is designed to …

Uav Path Planning In Complex Environments And Its Improved Artificial Rabbits Optimization Algorithm, Anlin Yin, Zhuhong Zhang

Journal of System Simulation

Abstract: The work probes into the model design of reliable and effective UAV path planning in complex obstacle environments and its related optimization algorithm. In the model design, a weight coefficient method and cylindrical coordinate system-based single-objective path planning model is developed to solve the UAV's flight path, in which the distance, angle, height and threat cost are taken as performance indices and obstacles in the ground and spatial regions are regarded as constraints. In the algorithm design, the SPM chaotic mapping is used to improve the initial population distribution of the artificial rabbit optimization algorithm in view of the …

Dynamic Scene Point Cloud Mapping Method Based On Lidar-Imu, Weigang Li, Lei Gan, Yongqiang Wang

Journal of System Simulation

Abstract: In order to address the issue of decreased mapping accuracy and precision caused by dynamic object interference during the construction of point cloud maps in dynamic scenarios such as urban roads, this study proposes a method for building dynamic scene point cloud maps based on LiDAR and inertial measurement unit (IMU). The method incorporates several key steps. An index-based Octree voxel structure is utilized to enhance the incremental update and nearest neighbor search efficiency of the local perception map (LP-Map). The point cloud is processed using ground segmentation, clustering, and dynamic score calculation methods to enable real-time identification of …

Performance Evaluation Technology For Low Earth Orbit Satellite Internet, Xiaofeng Wang, Yi Zhang, Guoxiu Zhang

Journal of System Simulation

Abstract: Performance evaluation can provide strong support for new technology verification of low earth orbit(LEO) satellite internet. Aiming at the characteristics of flexible networking and large spacetime scale of satellite internet, a performance evaluation architecture of satellite internet is designed. Aiming at the characteristics of various performance elements, a performance evaluation index system is designed under the premise of multi-dimensional comprehensive consideration. Aiming at the problem of frequent switching of satellite-ground links caused by high-speed movement, an algorithm for satelliteground link switching is proposed, which provides support for subsequent collection work. Aiming at the multi-dimensional problem of indicators, a multi-mode …

Simulation Research On Multi-Aircraft Conflict Resolution Based On Improved Chaotic Ant Colony Algorithm, Liang Tong, Jie Yang, Xusheng Gan, Di Shen, Wenda Yang, Daxiong Chen

Journal of System Simulation

Abstract: A chaotic ant colony algorithm based on dynamic volatility factor is proposed to solve the problem of multi-aircraft conflict resolution during free flight of fighter jets. The mathematical modelling is conducted on the conflict resolution problem of multiple fighter jets in the air. Based on the performance characteristics of fighter jets, fighter protection zone models, flight conflict models, and resolution models are established respectively. The chaotic ant colony algorithm is improved by using Logistic mapping and Henon mapping to optimize the pheromone update formula in the ant colony algorithm, and setting a dynamic factor for the pheromone volatilization factor …

Research On Mixed-Model Assembly Line Balancing Optimization Based On Hybrid Genetic Tabu Search Algorithm, Ke Wang, Sijia Guan, Xiyan Yin, Xixing Li, Hongtao Tang

Journal of System Simulation

Abstract: Aiming at the problem of unbalanced running load caused by idle or blocked workstations in the assembly line of mixed-flow hydraulic pump, a hybrid genetic tabu search algorithm solution and computer simulation verification method are proposed. A hybrid genetic tabu search algorithm with strong local search capability is designed with the optimization objectives of minimizing the production beats of the mixed-flow assembly line, the operational loads distributed among different workstations and the operational load smoothing indices of different products within the same workstation. The algorithm incorporates multi-fragment crossover and fragmentation of feasible solutions through Hamming distance mutation operations. The …

Research On The Digital Twin Architecture And Application Of Cnc System, Xiyang Zhang, Xusheng Lin, Rui Zhou, Yi Hu

Journal of System Simulation

Abstract: In response to the intelligent and digital requirements for virtual debugging, performance evaluation, and machining quality optimization of CNC systems in the field of production and manufacturing, a five dimensional digital twin system of CNC systems combining virtual and real is constructed based on digital twin technology. And combined with relevant new generation information technology, the digital twin system is modeled in multiple fields, including information models, mechanism models, and digital threads, to achieve comprehensive simulation and analysis of physical entities and processing processes. The study also verifies the feasibility of data transmission between CNC systems and digital twin …

Research And Implementation Of Digital Twin System For Mine Drainage Monitoring, Qinghui Wu, Yaqing Bao, Zhongxin Zhao, Xu Huang, Yuchen Wei

Journal of System Simulation

Abstract: The conventional mine drainage monitoring system faces problems such as poor visualization, insufficient linkage, and monotonous real-time monitoring methods for mine drainage in dynamic environments. Combining digital twin technology, a digital twin system for mine drainage monitoring has been developed. Through the construction of digital space, virtual real interaction layer structure framework, and three-dimensional visualization system data architecture, combined with fluid mechanics, using Unity3D development engine and five dimensional model ideas, a three-dimensional visualization system architecture for mine drainage is constructed, achieving various application functions such as real-time monitoring, fault warning, and virtual real mixed control. The feasibility of …

Design And Function Analysis Of New Steering System For Autonomous Vehicle, Peng Ji, Jinpeng Zhao, Limin Jiang

Journal of System Simulation

Abstract: For the current requirements of regulations and technical maturity, the steering system for autonomous vehicles must have the driver takeover function, explore the permanent magnet coupling device embedded in the steering system, and design a new steering system, which can realize the switch between automatic driving mode and driver takeover mode. The overall design of the new steering system is carried out. The system can realize the functions of steering wheel silence, road sense simulation, overload protection and mechanical steering redundancy, and realize the redundant design of steering system without adding additional hardware. The key component of the system, …

Research On Path Planning Method For Autonomous Underwater Vehicles Based On Improved Informed Rrt, Bensheng Qi, Yan Li, Hongxia Miao, Jialin Chen, Chenglin Li

Journal of System Simulation

Abstract: In response to the autonomous underwater vehicle (AUV) path planning problem in complex underwater environments, an improved path planning algorithm based on Informed rapidly-exploring random trees (RRT) is proposed in this study. A target-biased sampling strategy and a target-biased extension strategy are employed to address the issue of lack of goal orientation in the sampling process, ensuring that target nodes become sampling points during random sampling. During path points extension, non-target sampling points are guided in the direction of the target point, thereby enhancing the algorithm's ability to search for the target during random sampling and extension processes. A …

Path Planning Of Mobile Robot Based On The Integration Of Multi-Scale A* And Optimized Dwa Algorithm, Jianmin Xu, Lei Song, Dongdong Deng, Yaoruo Chen, Wei Yang

Journal of System Simulation

Abstract: In order to solve the problems of sharply increasing computational and time costs, as well as poor flexibility of the traditional A* algorithm and dynamic window approach (DWA) in the face of largescale complex environmental path planning, a fusion algorithm based on the A* algorithm of the multiscale map approach(MMA) and the improved DWA algorithm is proposed. A multi-scale map set is established and an obstacle proportion factor is added to the heuristic function of the A* algorithm. The A* algorithm is used to calculate the optimal path on the coarse-scale map, and the optimal path is mapped onto …

Feasibility And Acceptability Of The Mazi Umntanakho Digital Tool In South African Settings: A Qualitative Evaluation, Catherine E. Draper, Caylee J. Cook, Elizabeth A. Ankrah, Jesus A. Beltran, Franceli L. Cibrian, Kimberley D. Lakes, Hanna Mofid, Lucretia Williams, Gillian R. Hayes

Engineering Faculty Articles and Research

To address the need for interventions targeting social emotional development and mental health of young children in South Africa, the Mazi Umntanakho (‘know your child’) digital tool was co-designed, and piloted with caregivers and 3–5-year-old children involved in home visiting programmes promoting early childhood development. The aim of this study was to qualitatively evaluate the feasibility and acceptability of this tool in four urban and four rural low-income communities, from the perspective of home visitors and caregivers. Focus groups were conducted with home visitors (n = 117) and caregivers (n = 72). Issues relating to the feasibility of …

A Novel Mu-Metal Based Weak Magnetic Energy Harvester For Self-Powered Monitoring Of Power Grid Assets, Arsalan Habib Khawaja, Hassan Pervaiz, Dongsheng Cai, Jian Li, Qi Huang

Turkish Journal of Electrical Engineering and Computer Sciences

This paper presents a novel magnetic field driven contactless energy harvester with improved flux concentration capabilities for potential utilization in Power system monitoring where stray magnetic field is abundant and readily available. The designed harvester employs multilayered Mu-Metal based cone shaped core to maximize magnetic flux density. To achieve the final design, this work investigates magnetic flux concentration ability of various geometries and material properties in magnetic flux conditions typical to overhead 11 kV power distribution circuits. Impact of layers in core-coil region of harvesting coil on magnetic flux concentration is evaluated by means of Finite Element analysis. Resultantly, the …

Machine Learning Models Approach For The Quantitative Classification Of Ferricyanide Compound Using Electrochemical Detection With Cpe-Fe3o4nps, Süleyman Aşir, Nemah Abu Shama, Najya Maroof Saleem, Devri̇m Kayali, Kami̇l Di̇mi̇li̇ler

Turkish Journal of Electrical Engineering and Computer Sciences

Most common electrochemical analysis techniques used to evaluate enzymes, proteins, and heavy metals over a wide potential range include electrochemical impedance EIS, differential pulse voltammetry DPV, and square wave voltammetry SQWV. Machine leaning algorithms MLA are employed to classify the Potassium ferricyaniyde K3Fe(CN)6 concentrations using a modified carbon paste electrode CPE embedded with iron (II, III) oxide (Fe3O4) NPs. The CV, DPV, and SQWV voltametric data collected from all K3Fe(CN)6 concentrations were used as input data to the machine learning algorithms. Signaling current of K3Fe(CN)6 concentrations improved at Fe3O4 modified with nanoparticles NPs CPE in a comparison with the unmodified …

Balancing Anarchy And Efficiency: Partial Team Formations And Learning In Potential Games, Muhammed Sayin

Turkish Journal of Electrical Engineering and Computer Sciences

Non-cooperative multi-agent learning, focusing on individual rationality (anarchy), often falls short in achieving system-wide efficiency in potential games, a class of games with applications in decentralized control and optimization. On the other hand, cooperative approaches prioritize system efficiency but often via global coordination, which could be impractical, e.g., for large-scale and less controlled environments. To address this dilemma, we propose a novel framework that introduces partial team formations, allowing team members with shared objectives to coordinate their actions while maintaining team-wise rationality for improved system-wide efficiency without the burden of global coordination. We model such interactions as a multi-team game …

A Content-Based Recommender System For The Uav Caching In The Field Of Entertainment In Fog Computing, Elham Darbanian, Mohsen Nickray

Turkish Journal of Electrical Engineering and Computer Sciences

The Unmanned Aerial Vehicle (UAV) can be used as good flying base stations to cache popular content and follow a user mobility pattern, to help them in a suitable services. Conventional edge caching algorithms often prioritize cache contents with higher popularity. Nevertheless, the cache capacity of mobile devices is restricted, and diverse clients may have expansive varieties in content inclination designs. In this manner, the performance and effectiveness of the cache will be so constrained without great strategies. The composition of recommender system and edge caching is considered as a new research topic, which is used to reduce cost and …

Advanced Prediction Of Events And Temporal Expressions In Medical Text Using The Jena Api: Integrating Ontologies And Deep Learning, Hafida Tiaiba, Lyazid Sabri, Okba Kazar

Turkish Journal of Electrical Engineering and Computer Sciences

The automatic recognition of medical concepts and temporal expressions in narrative clinical text enhances the utility of electronic health records (EHRs) and supports clinical decision-making and research. However, challenges arise due to the complexity of medical language, ambiguity of terms, and variability in expression. To address these issues, the use of medical ontologies significantly improves data management in healthcare. A novel approach integrates various medical ontologies covering drugs, symptoms, diseases, anatomy, disease drivers, and food, and with convolutional neural networks (CNNs) -including Standard, Transposed, and Separable convolution models (CONSEPTR)- to extract both medical events (e.g., clinical departments, treatments, problems) and …

Dashar: An Implementation Of Augmented Reality Technology For Automotive Applications, Trevor D. Brown

Masters Theses & Specialist Projects

Since the advent of the modern automobile, manufacturers have provided means of tracking various critical data points associated with automobile operation, with the most prominent and standardized method being the instrument cluster. These data points include, but are not limited to, automobile speed, engine speed, fuel level, oil temperature, radiator (water) temperature, and battery charge. While this data is updated in real-time as the automobile is running, traditional instrument clusters cannot be modified or adjusted to the automobile driver’s needs, unless extensive after-market modifications are made. These modifications can be expensive, and require great understanding of the automobile’s assembly.

Alongside …

Environment And Intention Awareness For Navigation And Collaboration, Bhaskar Chandra Trivedi

Computer Science and Engineering Dissertations - Archive

Unmanned Aerial Systems (UAS) have become increasingly popular as versatile platforms for tasks such as surveillance, inspection, delivery, and maintenance. In many applications, UAS operate in environments frequented by people or containing sensitive infrastructure, which introduces physical risks in case of vehicle failure, as well as psychological and privacy concerns that may limit their acceptability. Ensuring safe and efficient operation thus requires that UAS consider these risks when planning navigation strategies. While prior information, such as city maps and building layouts, can partially inform risk assessment, such data is often incomplete, necessitating real-time augmentation of risk maps using sensor information. …

Design And Evaluation Of A Thai Speech Emotion Recognition Corpus With Ambiguous Annotations, Chompakorn Chaksangchaichot

Chulalongkorn University Theses and Dissertations (Chula ETD)

THAI-SER is the first large-scale Thai speech emotion recognition corpus, comprising 41.6 hours (27,854 utterances) from 100 recordings across diverse environments (Zoom and studio). The data includes both scripted and improvised speech by 200 professional actors (112 females, 88 males, aged 18–55), covering five emotions: neutral, angry, happy, sad, and frustrated. Utterances were labeled via crowdsourcing, with rigorous quality control ensuring a majority agreement score above 0.71. Annotation reliability, measured by Krippendorff’s alpha, reached 0.692 (above the 0.667 threshold), and human emotion recognition accuracy reached 0.772 after filtering. We also report benchmark results from models trained and evaluated on both …

Detection Of Data Leakage And Disruption Of Covert Timing Channel In Secure Drone Communication Using Machine And Deep Learning, Jonathan Walatkiewicz

Master's Theses and Doctoral Dissertations

The utilization of recreational drones has experienced a substantial increase in both the United States and globally. However, it is noteworthy that most drones, classified as Internet of Things devices, are produced with a limited security lifecycle. This study's findings are of paramount importance, as traditional computing exploits can be applied to drones, designating them as high- value targets. This study examines the detectability and disruptability of covert timing channel traffic in secure drones. The investigation aims to ascertain the effects of multiple interarrival times, distances ranging from 1 to 330 feet, various detection algorithms, and stream sizes between 32-bit …

Motion Planning For A Flexible Modular Raft Robot, Chun-Yi She

Dartmouth College Master’s Theses

This thesis presents a hierarchical motion planning framework for SoftRafts, a modular and deformable aquatic robot capable of performing locomotion and manipulation tasks on water surfaces. SoftRafts consist of soft and rigid components that enable structural reconfiguration, offering adaptability in unstructured aquatic environments.

To address the complexity of planning in high-dimensional, deformable systems, the proposed method uses a bounding-shape abstraction, specifically, enclosing circles and rectangular bounding boxes to simplify motion planning. These enclosures abstract the robot's overall shape, reducing the high-dimensional planning problem into a lower-dimensional problem. A global planner uses a probabilistic roadmap (PRM) to compute a collision-free path …

Insights In Cybersecurity Of A Smart Campus - A Review, Mircea Ţălu

Journal of Cybersecurity Education, Research and Practice

The profound impact of the Internet of Things (IoT) on various fronts, is driven by technological advancements, the ubiquitous spread of information, and the emergence of transformative events. IoT presents a diverse array of possibilities within university environments, fostering a more connected and enhanced educational experience. This research undertakes a comprehensive review of existing literature to provide context to the IoT and underscore its crucial significance in the realm of smart campuses. Additionally, the paper explores the intricate connections between IoT and key concepts such as cybersecurity and wireless sensor networks to present a holistic perspective. It delves into the …

‘Waves Of Imagination’ Unconditional Spectogram Diffusion Using Diffusion Architecture., Rahul Vanukuri

Computer Science and Engineering Theses - Archive

The swift evolution of wireless communication technologies,particularly in the field of rf signals or in CBRS bands,demands increasingly sophisticated signal processing techniques to ensure efficient transmission, reception, and spectrum management.Traditional approaches to signal generation and reconstruction, although effective in controlled environments, often struggle to cope with the challenges presented by real-world noisy conditions, hardware constraints, and limited access to large-scale datasets. In response to these limitations, this thesis explores the application of diffusion models—a class of generative models known for their ability to produce high-fidelity samples—to the domain of spectrogram generation for communication signals.

Different from conventional strategies to simulate …

การศึกษาแบบแผนการเต้นของหัวใจระหว่างการวิ่ง โดยใช้การเรียนรู้ของเครื่องแบบไม่มีผู้สอนเพื่อการตรวจจับความผิดปกติ, ชวิน หังสสูต

Chulalongkorn University Theses and Dissertations (Chula ETD)

การศึกษานี้มีวัตถุประสงค์เพื่อวิเคราะห์รูปแบบการเต้นของหัวใจระหว่างการวิ่ง โดยใช้เทคนิคการตรวจจับความผิดปกติแบบไม่มีผู้สอน (Unsupervised Anomaly Detection - UAD) เพื่อการตรวจจับความผิดปกติ ปัญหาหลักในงานวิจัยนี้คือข้อจำกัดทางจริยธรรมในการรวบรวมข้อมูลภาวะวิกฤตเพื่อใช้สอนแบบจำลอง และความแปรปรวนของข้อมูลสรีรวิทยาที่สูงมากระหว่างบุคคลเพื่อแก้ไขปัญหานี้ งานวิจัยนี้ได้พัฒนาระบบเว็บแอปพลิเคชันสำหรับการรวบรวมและกำกับข้อมูล โดยผู้เชี่ยวชาญ และได้สร้างชุดข้อมูลอ้างอิงจากกลุ่มตัวอย่างนักวิ่ง 5 ท่าน จากนั้น ได้ดำเนินการศึกษาเชิงเปรียบเทียบแบบจำลอง UAD จำนวน 7 แบบจำลอง โดยใช้กลยุทธ์การเรียนรู้แบบจำเพาะบุคคล ภายใต้เงื่อนไข การกำหนดค่าไฮเปอร์พารามิเตอร์แบบคงที่ เพื่อจำลองสถานการณ์การใช้งานจริงแบบเริ่มต้น โดยปราศจากการปรับแต่งค่าล่วงหน้า และประเมินผลด้วยค่า F0.5-Score เพื่อเน้นความแม่นยำและลดการแจ้งเตือนที่ผิดพลาดผลการทดลองพบว่า เมื่อไม่มีการปรับจูนพารามิเตอร์ ประสิทธิภาพโดยรวมของทุกแบบจำลองลดลงอย่างมีนัยสำคัญ ซึ่งสะท้อนถึงความท้าทายในการสร้างแบบจำลองสากล อย่างไรก็ตาม แบบจำลอง Matrix Profile (MP) ในกลุ่มคลาสสิก พิสูจน์ให้เห็นถึงความทนทานสูงที่สุด โดยมีประสิทธิภาพเฉลี่ยสูงสุด (F0.5-Score 2.71%) และสามารถตรวจจับความผิดปกติได้ดีในรายบุคคล ในขณะที่แบบจำลองพื้นฐานล้มเหลวโดยสิ้นเชิง (0.00%) สำหรับกลุ่มการเรียนรู้เชิงลึก (USAD, LSTM-AE) พบว่ามีข้อจำกัดในการใช้งานแบบเริ่มต้น (Cold-start) โดยไม่สามารถตรวจจับความผิดปกติได้แม้จะมีปริมาณข้อมูลมาก หากปราศจากการปรับแต่งค่าพารามิเตอร์ ผลลัพธ์นี้ยืนยันว่าระบบเฝ้าระวังสุขภาพในอนาคตจำเป็นต้องมีกลไกการเรียนรู้แบบปรับตัว ร่วมด้วยเพื่อให้สามารถนำไปใช้งานจริงได้อย่างมีประสิทธิภาพ

การคาดการณ์ค่าดัชนีความแตกต่างของพืชและความชื้น โดยใช้เทคนิคการเรียนรู้ของเครื่องอย่างชาญฉลาด เพื่อการติดตามด้านการเกษตรและสิ่งแวดล้อม, ณุทยา เข็มเจริญ

Chulalongkorn University Theses and Dissertations (Chula ETD)

ปัจจุบัน ภัยแล้งและการเปลี่ยนแปลงสภาพภูมิอากาศส่งผลกระทบต่อผลผลิตทางการเกษตร โดยเฉพาะพืชเศรษฐกิจของไทยอย่างทุเรียน ซึ่งต้องอาศัยการติดตามสุขภาพพืชและการจัดการน้ำอย่างใกล้ชิด ข้อมูลจากภาพถ่ายดาวเทียม ดัชนีความแตกต่างของพืชและความชื้น จึงเป็นเครื่องมือสำคัญในการวิเคราะห์สภาพพื้นที่เพาะปลูก โครงงานนี้พัฒนาแบบจำลองการเรียนรู้ของเครื่องเพื่อพยากรณ์ทั้งสองดัชนีรายสัปดาห์ โดยใช้การเฉลี่ยและเติมค่าข้อมูลที่ขาดหายด้วยการถดถอยเชิงเส้น ก่อนนำไปฝึกแบบจำลองผสมระหว่างโครงข่ายคอนโวลูชัน และหน่วยความจำระยะสั้นแบบยาว ระบบถูกออกแบบให้ทำงานอัตโนมัติภายใต้แนวคิดการปฏิบัติการด้านการเรียนรู้ของเครื่อง แสดงผลผ่านเว็บแอปพลิเคชัน ติดตั้งและทดสอบบนเครื่องเซิร์ฟเวอร์

Automated Infinite Combos Detection System For Collectible Card Game, Amornpong Trakarnkulphun

Chulalongkorn University Theses and Dissertations (Chula ETD)

In Collectible Card Games, resources management is one of the most effective strategy. However, there are some combinations of cards which produce unlimited resources called infinite combos. Too-cheap infinite combos that can be played early in the game break game environment, because the player who executes the combo immediately wins. To solve the problem, game designers usually restrict a part of the combos from being played. Due to the large number of cards in the card pool, it is difficult to search for these combos and solve this problem before a release date of a card set. This research aims …