Academic Platform Journal of Engineering and Smart Systems最新文献

Genetically Tuned Linear Quadratic Regulator for Trajectory Tracking of a Quadrotor 用于四旋翼飞行器轨迹跟踪的基因调谐线性二次调节器

Academic Platform Journal of Engineering and Smart Systems Pub Date : 2024-01-31 DOI: 10.21541/apjess.1316025

A. T. Karaşahin

{"title":"Genetically Tuned Linear Quadratic Regulator for Trajectory Tracking of a Quadrotor","authors":"A. T. Karaşahin","doi":"10.21541/apjess.1316025","DOIUrl":"https://doi.org/10.21541/apjess.1316025","url":null,"abstract":"In this paper, a linear quadratic regulator (LQR) controller operating according to the genetically tuned inner-outer loop structure is proposed for trajectory tracking of a quadrotor. Setting the parameters of a linear controller operating according to the inner-outer loop structure is a matter that requires profound expertise. Optimization algorithms are used to cope with the solution of this problem. First, the dynamic equations of motion of the quadrotor are obtained and modelled in state-space form. The LQR controller, which will operate according to the inner-outer loop structure in the MATLAB/Simulink environment, has been developed separately for 6 degrees of freedom (DOF) of the quadrotor. Since adjusting these parameters will take a long time, a genetic algorithm has been used at this point. The LQR controller with optimized coefficients and a proposed LQR controller-based study in the literature are evaluated according to their success in following the reference trajectory and their responses to specific control inputs. According to the results obtained, it was observed that the genetically adjusted LQR controller produced more successful outcomes.","PeriodicalId":472387,"journal":{"name":"Academic Platform Journal of Engineering and Smart Systems","volume":"36 12","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140479010","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

IoT-based Smart Home Security System with Machine Learning Models 基于物联网的智能家居安防系统与机器学习模型

Academic Platform Journal of Engineering and Smart Systems Pub Date : 2024-01-31 DOI: 10.21541/apjess.1236912

Selman Hizal, Ü. Çavuşoğlu, D. Akgün

{"title":"IoT-based Smart Home Security System with Machine Learning Models","authors":"Selman Hizal, Ü. Çavuşoğlu, D. Akgün","doi":"10.21541/apjess.1236912","DOIUrl":"https://doi.org/10.21541/apjess.1236912","url":null,"abstract":"The Internet of Things (IoT) has various applications in practice, such as smart homes and buildings, traffic management, industrial management, and smart farming. On the other hand, security issues are raised by the growing use of IoT applications. Researchers develop machine learning models that focus on better classification accuracy and decreasing model response time to solve this security problem. In this study, we made a comparative evaluation of machine learning algorithms for intrusion detection systems on IoT networks using the DS2oS dataset. The dataset was first processed to feature extraction using the info gain attribute evaluation feature extraction approach. The original dataset (12 attributes), the dataset (6 attributes) produced using the info gain approach, and the dataset (11 attributes) obtained by eliminating the timestamp attribute was then formed. These datasets were subjected to performance testing using several machine learning methods and test choices (crossfold-10, percentage split). The test performance results are presented, and an evaluation is performed, such as accuracy, precision, recall, and F1 score. According to the test results, it has been observed that high accuracy detection rates are achieved for IoT devices with limited processing power.","PeriodicalId":472387,"journal":{"name":"Academic Platform Journal of Engineering and Smart Systems","volume":"17 7","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140477500","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

AI-Embedded UAV System for Detecting and Pursuing Unwanted UAVs 人工智能嵌入式无人机系统，用于检测和追捕不受欢迎的无人机

Academic Platform Journal of Engineering and Smart Systems Pub Date : 2024-01-31 DOI: 10.21541/apjess.1349856

Ali Furkan Kamanlı

{"title":"AI-Embedded UAV System for Detecting and Pursuing Unwanted UAVs","authors":"Ali Furkan Kamanlı","doi":"10.21541/apjess.1349856","DOIUrl":"https://doi.org/10.21541/apjess.1349856","url":null,"abstract":"In recent years, the use of unmanned aerial vehicle (UAV) platforms in civil and military applications has surged, highlighting the critical role of artificial intelligence (AI) embedded UAV systems in the future. This study introduces the Autonomous Drone (Vechür-SIHA), a novel AI-embedded UAV system designed for real-time detection and tracking of other UAVs during flight sequences. Leveraging advanced object detection algorithms and an LSTM-based tracking mechanism, our system achieves an impressive 80% accuracy in drone detection, even in challenging conditions like varying backgrounds and adverse weather. \u0000Our system boasts the capability to simultaneously track multiple drones within its field of view, maintaining flight for up to 35 minutes, making it ideal for extended missions that require continuous UAV tracking. Moreover, it can lock onto and track other UAVs in mid-air for durations of 4-10 seconds without losing contact, a feature with significant potential for security applications. \u0000This research marks a substantial contribution to the development of AI-embedded UAV systems, with broad implications across diverse domains such as search and rescue operations, border security, and forest fire prevention. These results provide a solid foundation for future research, fostering the creation of similar systems tailored to different applications, ultimately enhancing the efficiency and safety of UAV operations. The novel approach to real-time UAV detection and tracking presented here holds promise for driving innovations in UAV technology and its diverse applications.","PeriodicalId":472387,"journal":{"name":"Academic Platform Journal of Engineering and Smart Systems","volume":"192 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140470788","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Determination of Electricity Production by Fuzzy Logic Method 用模糊逻辑法确定发电量

Academic Platform Journal of Engineering and Smart Systems Pub Date : 2024-01-31 DOI: 10.21541/apjess.1326975

Beyza Özdem, Muharrem Dügenci, M. İpek

{"title":"Determination of Electricity Production by Fuzzy Logic Method","authors":"Beyza Özdem, Muharrem Dügenci, M. İpek","doi":"10.21541/apjess.1326975","DOIUrl":"https://doi.org/10.21541/apjess.1326975","url":null,"abstract":"With the increase in the need for electrical energy, production amount planning is of great importance in order not to experience restrictions in terms of use, to meet the required electricity production, and to evaluate the excess production efficiently. In this study, a generation forecasting model was created with the fuzzy logic method to determine the electricity generation strategy. The created model is aimed to determine the electrical energy that needs to be produced daily by using the previous day's production amount, temperature, and season data. Three separate sets of data were used to test the fuzzy logic model built using information from the General Directorate of Meteorology (GDM) and Energy Markets Operations Inc. (EMOI). Fuzzy Logic was used to predict the data and the accuracy rates were found to be high. An improvement was observed when the accuracy rates were compared with the accuracy rates obtained in the Multiple Linear Regression Model. The accuracy rates of the model were initially examined using the Fuzzy Logic approach on weekdays and weekends, followed by a seasonal analysis and an assessment of the model's performance. As a result of the analysis, it was observed that the model worked with high accuracy in the autumn season and on weekend days.","PeriodicalId":472387,"journal":{"name":"Academic Platform Journal of Engineering and Smart Systems","volume":"38 5","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140479202","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Statistical and Artificial Intelligence Based Forecasting Approaches for Cash Demand Problem of Automated Teller Machines 基于统计和人工智能的自动柜员机现金需求问题预测方法

Academic Platform Journal of Engineering and Smart Systems Pub Date : 2024-01-31 DOI: 10.21541/apjess.1360151

M. Cedolin, Deniz Orhan, M. Genevois

{"title":"Statistical and Artificial Intelligence Based Forecasting Approaches for Cash Demand Problem of Automated Teller Machines","authors":"M. Cedolin, Deniz Orhan, M. Genevois","doi":"10.21541/apjess.1360151","DOIUrl":"https://doi.org/10.21541/apjess.1360151","url":null,"abstract":"The efficient management of cash replenishment in Automated Teller Machines (ATMs) is a critical concern for banks and financial institutions. This paper explores the application of statistical and artificial intelligence (AI) forecasting methods to address the cash demand problem in ATMs. Recognizing the significance of accurate cash predictions for ensuring uninterrupted ATM services and minimizing operational costs, we investigate various forecasting approaches. Initially, statistical methodologies including Autoregressive Integrated Moving Average (ARIMA) and Seasonal ARIMA (SARIMA) are employed to model and forecast cash demand patterns. Subsequently, machine learning techniques such as Deep Neural Networks (DNN) and Prophet algorithm are leveraged to enhance prediction accuracy. We assess the performance of these methodologies through rigorous analysis and evaluation. Furthermore, the paper delves into the integration of these forecasting approaches within an overall decision support system for ATM cash management. By optimizing cash replenishment strategies based on accurate forecasts, financial institutions aim to simultaneously enhance customer satisfaction and reduce operational expenses. The findings of this study contribute to a comprehensive understanding of how statistical and AI-driven forecasting can revolutionize cash management in ATMs, offering insights for improving the efficiency and cost-effectiveness of ATM services in the banking sector.","PeriodicalId":472387,"journal":{"name":"Academic Platform Journal of Engineering and Smart Systems","volume":"121 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140477182","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Is ChatGPT Leading Generative AI? What is Beyond Expectations? ChatGPT是生成式AI的领导者吗?什么是超出预期?

Academic Platform Journal of Engineering and Smart Systems Pub Date : 2023-09-30 DOI: 10.21541/apjess.1293702

Ömer AYDIN, Enis KARAARSLAN

{"title":"Is ChatGPT Leading Generative AI? What is Beyond Expectations?","authors":"Ömer AYDIN, Enis KARAARSLAN","doi":"10.21541/apjess.1293702","DOIUrl":"https://doi.org/10.21541/apjess.1293702","url":null,"abstract":"Generative AI has the potential to change the way we do things. The chatbot is one of the most popular implementation areas. Even though companies like Google and Meta had chatbots, ChatGPT became popular as it was made publicly available. Although ChatGPT is still in the early stages of its development, it attracted the attention of people and capital groups. It has taken the public interest; people from different fields, ages, and education levels started using ChatGPT. There have been many trials with ChatGPT. It is possible to see a lot of news and shares on the Internet. The study aims to shed light on what is happening in the literature and get an insight into the user expectations of ChatGPT and Generative AI. We also give information about the competitors of ChatGPT, such as Google’s Bard AI, Claude, Meta’s Wit.ai and Tencent’s HunyuanAide. We describe technical and structural fundamentals and try to shed light on who will win the race. We also shared information about the GPT4 version of OpenAI's ChatGPT. We share the early stage due diligence and current situation analysis for all these points. We examine preprint papers and published articles. We also included striking posts on the LinkedIn platform and a compilation of various blogs and news. We also made use of ChatGPT in editing the content of these resources of this study. We can get an insight into the people's interests through their questions submitted to ChatGPT. We can also understand the capabilities of GPT3, GPT4 and also predict further enhancements.","PeriodicalId":472387,"journal":{"name":"Academic Platform Journal of Engineering and Smart Systems","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136271507","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Artificial Neural Networks-Based Route Selection Model for Multimodal Freight Transport Network During Global Pandemic 基于人工神经网络的全球流行病多式联运网络路线选择模型

Academic Platform Journal of Engineering and Smart Systems Pub Date : 2023-09-30 DOI: 10.21541/apjess.1294957

Yaşanur KAYIKCI, Elif CESUR

{"title":"Artificial Neural Networks-Based Route Selection Model for Multimodal Freight Transport Network During Global Pandemic","authors":"Yaşanur KAYIKCI, Elif CESUR","doi":"10.21541/apjess.1294957","DOIUrl":"https://doi.org/10.21541/apjess.1294957","url":null,"abstract":"The global pandemic caused major disruptions in all supply chains. Road transport has been particularly affected by the challenges posed by the COVID-19 pandemic. The selection of an efficient and effective route in multimodal freight transport networks is a crucial part of transport planning to combat the challenges and sustain supply chain continuity in the face of the global pandemic. This study introduces a novel optimal route selection model based on integrated fuzzy logic approach and artificial neural networks. The proposed model attempts to identify the optimal route from a range of feasible route options by measuring the performance of each route according to transport variables including, time, cost, and reliability. This model provides a systematic method for route selection, enabling transportation planners to make smart decisions. A case study is conducted to exhibit the proposed model's applicability to real pandemic conditions. According to the findings of the study, the proposed model can accurately and effectively identify the best route and provides transportation planners with a viable option to increase the efficiency of multimodal transport networks. In conclusion, by proposing an innovative and efficient strategy for route selection in complex transport systems, our research significantly advances the field of transportation management.","PeriodicalId":472387,"journal":{"name":"Academic Platform Journal of Engineering and Smart Systems","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136271670","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Novel Clustering-based Forecast Framework: The Clusters with Competing Configurations Approach 一种新的基于聚类的预测框架:竞争配置聚类方法

Academic Platform Journal of Engineering and Smart Systems Pub Date : 2023-09-30 DOI: 10.21541/apjess.1266610

Miray ALP, Gökhan DEMİRKIRAN

{"title":"A Novel Clustering-based Forecast Framework: The Clusters with Competing Configurations Approach","authors":"Miray ALP, Gökhan DEMİRKIRAN","doi":"10.21541/apjess.1266610","DOIUrl":"https://doi.org/10.21541/apjess.1266610","url":null,"abstract":"Accurate aggregate (total) short-term load forecasting of Smart Homes (SHs) is essential in planning and management of power utilities. The baseline approach consists of simply designing and training predictors for the aggregated consumption data. Nevertheless, better performance can be achieved by using a clustering-based forecasting strategy. In such strategy, the SHs are grouped according to some metric and the forecast of each group's total consumption are summed to reach the forecast of aggregate consumption of all SHs. Although the idea is simple, its implementation requires fine-detailed steps. This paper proposes a novel clustering-based aggregate-level forecast framework, so called Clusters with Competing Configurations (CwCC) approach and then compares its performance to the baseline strategy, namely Clusters with the Same Configurations (CwSC) approach. The Configurations in the name refers to the configurations of ARIMA, Multi-Layer Perceptron (MLP), and Long Short-Term Memory (LSTM) forecasting methods, which the CwCC approach uses. We test the CwCC approach on Smart Grid Smart City Dataset. The results show that better performance can be achieved using the CwCC approach for each of the three forecast methods, and LSTM outperforms other methods in each scenario.","PeriodicalId":472387,"journal":{"name":"Academic Platform Journal of Engineering and Smart Systems","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136271506","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Human Activity Recognition with Smartwatch Data by using Mahalanobis Distance-Based Outlier Detection and Ensemble Learning Methods 基于Mahalanobis距离离群点检测和集成学习方法的智能手表数据人类活动识别

Academic Platform Journal of Engineering and Smart Systems Pub Date : 2023-09-30 DOI: 10.21541/apjess.1105362

Serkan BALLI, Ensar Arif SAĞBAŞ

{"title":"Human Activity Recognition with Smartwatch Data by using Mahalanobis Distance-Based Outlier Detection and Ensemble Learning Methods","authors":"Serkan BALLI, Ensar Arif SAĞBAŞ","doi":"10.21541/apjess.1105362","DOIUrl":"https://doi.org/10.21541/apjess.1105362","url":null,"abstract":"Recognition of human activities is part of smart healthcare applications. In this context, the detection of human actions with high accuracy has been a field that has been working for many years. With the increase in the usage of smart devices, smartphones and smartwatches have become the constant equipment of these studies thanks to their internal sensors. Sometimes abnormal data are included in data sets due to the way the data were collected and for reasons arising from the sensors. For this reason, it becomes important to detect outlier data. In this study, step counter and heart rate sensors were used in addition to an accelerometer and gyroscope in order to detect human activities. Afterward, the outliers were detected and cleared with a Mahalanobis distance-based approach. With the aim of achieving a better classification performance, machine learning methods were used by strengthening them with ensemble learning methods. The obtained results showed that step counter, heart rate sensors, and ensemble learning methods positively affect the success of the classification. In addition, it was found that the Mahalanobis distance-based outlier detection method increased the classification accuracy significantly.","PeriodicalId":472387,"journal":{"name":"Academic Platform Journal of Engineering and Smart Systems","volume":"67 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136271505","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Optimizing PID Gains of a Vehicle using the state-of-the-art Metaheuristic Methods 用最先进的元启发式方法优化车辆的PID增益

Academic Platform Journal of Engineering and Smart Systems Pub Date : 2023-09-30 DOI: 10.21541/apjess.1266949

Mustafa Atakan AFŞAR, Hilal ARSLAN

{"title":"Optimizing PID Gains of a Vehicle using the state-of-the-art Metaheuristic Methods","authors":"Mustafa Atakan AFŞAR, Hilal ARSLAN","doi":"10.21541/apjess.1266949","DOIUrl":"https://doi.org/10.21541/apjess.1266949","url":null,"abstract":"PID controllers are important control methods that are widely used in industrial processes. Proper tuning of PID gains is critical for achieving the state-of-the-art system performance. Therefore, optimizing PID gains is an important research topic in the field of control engineering. In this study, PID controller gains are automatically tuned using metaheuristic optimization methods. These methods use an iterative approach to calculate optimal values of PID controller gains based on different optimization techniques. The interaction between artificial intelligence and control systems requires a multidimensional approach across different disciplines. In the study, we perform Particle Swarm Optimization, Gray Wolf Optimization, Whale Optimization Algorithm, Firefly Algorithm, Harris Hawks Optimization, Artificial Hummingbird Algorithm and African Vulture Optimization Algorithm to determine PID gains. In the simulation, step input is applied to the dynamic equation of the unmanned free-swimming submersible vehicle. The fitness function is determined with respect to controller integral square error, settling time value, and maximum percent overshoot value. We also evaluate the optimization time of the selected algorithms based on the fitness function. Experimental results present that Artificial Hummingbird Algorithm, Gray Wolf Optimization and Particle Swarm Optimization achieve significant performance. This underlines that using metaheuristic methods in PID gain optimization increase overall system performance.","PeriodicalId":472387,"journal":{"name":"Academic Platform Journal of Engineering and Smart Systems","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136272253","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0