Polygon Method Research Articles

A Tri-Level Transaction Method for Microgrid Clusters Considering Uncertainties and Dynamic Hydrogen Prices

The advancement of hydrogen technology and rising environmental concerns have shifted research toward renewable energy for green hydrogen production. This study introduces a novel tri-level transaction methodology for microgrid clusters, addressing uncertainties and price fluctuations in hydrogen. We establish a comprehensive microgrid topology with distributed power generation and hydrogen production facilities. A polygonal uncertainty set method quantifies wind and solar energy uncertainties, while an enhanced interval optimization technique refines the model. We integrate a sophisticated demand response model for hydrogen loading, capturing users’ behavior in response to price changes, thereby improving renewable energy utilization and supporting economically viable management practices. Additionally, we propose a tri-level game-theoretic framework for analyzing stakeholder interactions in microgrid clusters, incorporating supply–demand dynamics and a master–slave structure for microgrids and users. A distributed algorithm, “KKT & supply-demand ratio”, solves large-scale optimization problems by integrating Karush–Kuhn–Tucker conditions with a heuristic approach. Our simulations validate the methodology, demonstrating that accounting for uncertainties and dynamic hydrogen prices enhances renewable energy use and economic efficiency, optimizing social welfare for operators and economic benefits for microgrids and users.

Suitability techniques for transforming marginal lands to support building infrastructures in parts of Rivers State, Nigeria

This study examined sustainability techniques for transforming marginal lands to support building infrastructures in parts of Rivers State, Nigeria. The study adopted the cross-sectional survey research design method employing the use of standard penetration approach utilizing Geographic Information System analysis. Marginal lands were delineated as margins of watrbodies using the polygon method in ArcGIS, and were created as a feature class for polygon data (shape file). The locations, river margins and roads formed point data, polygon data and line data respectively. Digitisation was achieved using Orthophoto Image in ArcGIS 10.0 software where seven geotechnical boreholes were located and drilled using permission rig to a depth of 10.5m in five local government areas of Rivers State. In-situ standard penetration testing and soil sampling for laboratory geotechnical properties was done using standard laboratory techniques. Findings of the analysis show that silty and sandy clay are the dominant soil within the foundation depth of 1-2.5m which are underlained by clays and sands of varying densities and grain sizes with their specific gravity value of ranges of 1.9 – 2.66 depicting that the areas are underlined by organic, diatomaceous and high porosity permeability soils deposits under water logged conditions. The cohesive strength of the soils vary from 65KN/m 2 - 115KN/m 2, angle of internal friction ranged from 0o – 10o and shear strength ranged from 110KN/m 2 – 147.46KN/m 2 and the allowable bearing capacities of 180.22KN/m 2 – 236.05KN/m 2. The stability techniques for the transformation of the land to support building infrastructures are pre-construction soil stabilization and marginal land reinforcement. The study thus recommends for building summation of consolidated techniques for sustainability of infrastructures.

SPATIAL ANALYSIS OF PHYSICAL ACCESSIBILITY TO PUBLIC PRIMARY HEALTHCARE CENTERS IN KADUNA STATE, NIGERIA

The rising call for spatial justice in the distribution and access to public facilities especially health necessitated this study. The study sets out to assess the spatial patterns of physical accessibility to PPHCs in Kaduna State. Four physical accessibility parameters were used in this study: travel time, travel distance to the nearest Public Primary Healthcare Centers (PPHCs), mean distances between and within PPHCs, and effective geographic catchment area coverage of PPHCs. Both travel time and distance to the nearest PPHC were evaluated using a questionnaire. The mean distance between and within PPHCs for LGAs was estimated from the Nearest Neighbor Analysis. The effective geographic catchment area of a PPHC was determined using the geospatial Thiessen polygon method. Findings showed that 42% of the respondents, live close (< 2 km) to a PPHC facility. The proximity of the respondents from Igabi (52%), Zaria (49%), and Zangon-Kataf (51%) is closer than the other LGAs. Thiessen catchment area showed a wide range of variations with some PPHCs with very large areas (426 -615 km2) mostly found in the central senatorial zone, especially in Birnin Gwari and Chikun LGAs. The most widespread are PPHCs with relatively moderate catchment sizes of (187–339 km2) found across parts of northern, central, and southern senatorial and LGAs. The study concludes that areal and topographic factors as revealed by the polygon-derived catchment areas should also guide the decision for the siting of PPHCs in the state. Hence, additional PPHCs are recommended especially LGAs with extensive land masses.

Ámbito de hogar, preferencia de hábitat y patrones de actividad del zorro de Sechura Lycalopex sechurae (Mammalia: Canidae) en el Desierto de Sechura, noroeste del Perú

The Sechura fox (Lycalopex sechurae) is a little-studied species despite being common in northwestern Peru and listed as Near Threatened internationally. This study presents the home range, habitat preference, and activity patterns of L. sechurae in two locations of the Sechura Desert: The Mangroves of San Pedro de Vice (MSPV) and the Illescas National Reserve (RNI). Using GPS collars, the minimum convex polygon method, and the Kernel estimator (KE), the home range of four female individuals (two from each site) was calculated. Additionally, the GPS location data were used to estimate activity patterns and habitat preferences for each individual. The home range of females from MSPV was 0.6 and 1 km² (95% KE), whereas, for the RNI, it was 3.5 and 25.1 km² (95% KE). Females from MSPV preferred dry forest (54.8% and 76.1%), while those from RNI favored desert scrub (64.3% and 64.5%). All individuals exhibited cathemeral behavior, with increased nocturnal activity. Our results demonstrate variability in home range sizes, similarity in activity patterns compared to other studies, and highlight the importance of dry forest and desert scrub as resource-rich habitats for Lycalopex sechurae.

Post-release dispersal and home range of translocated red deer in the Vojvodina province (Serbia)

Monitoring of 38 (12 male and 26 female) red deer translocated from Ivo Wildlife Park (Romania) to hunting ground "Bosutske Forest" (Vojvodina, Serbia) was conducted from 2017 to 2021. The red deer were translocated in lieu of the managing authority's efforts to counteract the effects of red deer losses due to catastrophic flooding in the region. All animals were ear-tagged, while 7 males and 10 females were fitted with GPS collars. A total of 2,288 valid signals were analyzed (565 from males and 1,723 from females). In addition, 1,333 sighting records were collected from eight observation posts (480 in 2019, 670 in 2020 and 183 in 2021). We determined the movements and spatial distribution of translocated animals in the new habitat and estimated their home range sizes. Home range was calculated using the minimum convex polygon method, while the core area was calculated using the kernel density estimator method. The greatest straight-line distance from the acclimatisation enclosure was essentially the same for both sexes (average 6.0 km for males and 6.4 km for females). A non-significant relationship existed between the number of days in captivity and the greatest straight-line distance, as well as between days in captivity and the core area of the home range. The estimated home range of males was 12.8 km2 (range 0.2‒36.1), smaller than that of females (20.6 km2, range 0.4‒68.7), but this difference was not statistically significant. Observations made independently showed mostly herds of 4 to 6 individuals (52.3%), while large herds (≥ 10 individuals) were rare. Participation of translocated and resident animals in mixed herds was common during the monitoring period (62.3%). Our results showed that a high level of acceptance of the new habitat and social cohesion between translocated and resident animals was achieved. We believe that this is due to two main reasons: firstly, the long-term stay in a large acclimatisation enclosure prior to release and secondly, year-round supplemental feeding coupled with an abundant natural food supply in this unique forest area also contributed to successful acclimatisation. Keywords: Cervus elaphus; population; habitat; home range size; red deer; management

Research on mobile energy storage scheduling strategy for emergency power supply protection of post-disaster isolated loads

Aiming at the problem of insufficient power supply capacity of isolated loads in oceanic islands, a concept based on mobile energy storage and power conservation is proposed in this paper. Firstly, the energy flow and traffic flow characteristics of mobile energy storage are quantitatively analyzed, and an accurate mathematical model is established. Furthermore, the time-space distribution characteristics of load are carefully considered, and the Voronoi diagram and Tyson polygon method are introduced to determine cell differentiation. On this basis, combined with the power demand of load nodes and the energy storage characteristics of mobile energy storage vehicles, the evaluation indicators of cell energy and relative surplus energy of cells are designed, and the agent-cellular automata algorithm is used to schedule the mobile energy storage. The simulation results show that the power supply mode based on mobile energy storage can effectively improve the reliability of isolated loads. This paper provides a new perspective for solving the reliable power supply problem of isolated loads.

A comparison of home range estimates using the time local convex hull (T‐LoCoH) and minimum convex polygon (MCP) methods for African savannah elephants in a semi‐arid protected area

A comparison of home range estimates using the time local convex hull (T‐LoCoH) and minimum convex polygon (MCP) methods for African savannah elephants in a semi‐arid protected area

Polygonal plate element method for free vibration analysis using an efficient alpha (α)-assumed rotations and shear strains

This paper investigates the performance of a recently proposed polygonal plate element with alpha (α)-assumed rotations and shear strains, referred to as αARS-Poly, in free vibration analysis. The αARS-Poly element utilizes a simple and efficient approach involving a scaling factor (α) to enhance the accuracy of assumed rotations and shear strains. To fully explore the advantages of this element, we undertake a comprehensive analysis of free vibration in plate structures using a range of models with complex geometries. Numerical results demonstrate that the αARS-Poly element offers stability and reliability within smooth mode shapes. Furthermore, it significantly outperforms the previous polygonal Reissner-Mindlin plate element with piecewise-linear shape functions (PRMn-PL), achieving frequencies that closely match reference solutions, thereby validating its accuracy and robustness for dynamic applications.

Fatigue crack growth in functionally graded materials using an adaptive phase field method with cycle jump scheme

Functionally graded materials provide versatility in adjusting the volume fractions of constituent materials to meet specific design requirements. However, this customization often introduces mode-mixity at the crack tip, posing challenges in predicting fracture under cyclic loading with discrete approaches and computationally expensive with conventional phase-field fracture models. To address these issues, this paper introduces an adaptive phase-field fracture formulation with cycle jump scheme to elegantly predict fatigue crack nucleation and growth in functionally graded materials. Within this framework, the effective properties at a point are estimated using the Mori–Tanaka homogenization scheme, while the crack growth due to cyclic load is captured by incorporating an additional fatigue degradation parameter. Moreover, the computational efficiency of the proposed framework is improved through an adaptive mesh refinement and explicit cycle jump scheme. The adaptive refinement scheme utilizes an error indicator derived from both the displacement solution and phase-field variable. The adaptive refinement scheme is integrated with efficient quadtree decomposition, which generates a hierarchical mesh structure. Hanging nodes resulting from the quadtree decomposition are efficiently handled using a polygonal finite element method. The proposed framework is validated against experimental and numerical results reported in the literature. Furthermore, we investigate the fatigue crack growth resistance across a broad range of material gradation directions, gaining valuable insights and identifying functionally graded materials with high fatigue resistance.

Dead-reckoning facilitates determination of activity and habitat use: a case study with European badgers (Meles meles)

BackgroundStudies describing the movement of free-ranging animals often use remotely collected global positioning system (GPS) data. However, such data typically only include intermittent positional information, with a sampling frequency that is constrained by battery life, producing sub-sampling effects that have the potential to bias interpretation. GPS-enhanced ‘dead-reckoning’ of animal movements is an alternative approach that utilises combined information from GPS devices, tri-axial accelerometers, and tri-axial magnetometers. Continuous detailed information of animal movement, activity and habitat selection can then be inferred from finer-scale GPS-enhanced dead-reckoning. It is also a useful technique to reveal the minutiae of an animal’s movements such as path tortuosity. However, examples of studies using these approaches on terrestrial species are limited.MethodsCollars equipped with GPS, tri-axial accelerometer, and tri-axial magnetometer loggers were deployed on European badgers, Meles meles, to collect data on geo-position, acceleration and magnetic compass heading, respectively. This enabled us to compare GPS data with calculated GPS-enhanced dead-reckoned data. We also examined space use, distances travelled, speed of travel, and path tortuosity in relation to habitat type.ResultsNightly distances travelled were 2.2 times greater when calculated using GPS-enhanced dead-reckoned data than when calculated using GPS data alone. The use of dead-reckoned data reduced Kernel Density Estimates (KDE) of animal ranges to approximately half the size (0.21 km2) estimated using GPS data (0.46 km2). In contrast, Minimum Convex Polygon (MCP) methods showed that use of dead reckoned data yielded larger estimates of animal ranges than use of GPS-only data (0.35 and 0.27 km2, respectively).Analyses indicated that longer periods of activity were associated with greater travel distances and increased activity-related energy expenditure. Badgers also moved greater distances when they travelled at faster speeds and when the routes that they took were less tortuous. Nightly activity-related energy expenditure was not related to average travel speed or average ambient temperature but was positively related to the length of time individuals spent outside the sett (burrow). Badger activity varied with habitat type, with greater distance, speed, track tortuosity, and activity undertaken within woodland areas. Analyses of the effects of varying GPS sampling rate indicate that assessments of distance travelled depend on the sampling interval and the tortuosity of the animal’s track. Where animal paths change direction rapidly, it becomes more important to use dead-reckoned data rather than GPS data alone to determine space use and distances.ConclusionsThis study demonstrates the efficacy of GPS-enhanced dead-reckoning to collect high-resolution data on animal movements, activity, and locations and thereby identify subtle differences amongst individuals. This work also shows how the temporal resolution of position fixes plays a key role in the estimation of various movement metrics, such as travel speed and track tortuosity.

Utilization of Open Polygon Method for Land Mapping in Mojoroto Kediri with Geospatial Approach

Land mapping is an important research activity to determine the location of points on the earth's surface, describing the physical condition of parts of the surface that resemble the actual condition. The objective of this process is to gain a comprehensive understanding of the land to be built and used through land area measurements, topographic maps, and land volume analysis at various altitudes. In this mapping, the open polygon method is used for calculations which are conventional methods using data point values as data centers to represent the area of influence. During this mapping, there are three main points used with the open polygon method. A total of 26 ground contours were recorded, and 4 road contours recorded. During the mapping process, corrections are required on the open polygon calculations to ensure the accuracy of the results. This correction involves adjusting the data to take into account field variability and inaccuracies of measuring instruments, so that the resulting data can be reliable for further analysis and correct decision-making. The land that has been painted can be used for various fields such as construction, and mining. Land mapping allows partial surface physical state imaging, classification of land, and can be used to plan, build, and maintain infrastructure such as highways and bridges. The result of this practice obtained data of the maximum height of 90,0945 masl and minimum 88,76 masl with the average ground height 90,05059 masl, while the average highway height is at 88,86175 masl.

Assessment of area at risk of flood and drought in the SeThamok Sub-basin

The problem of floods and drought is a serious problem and has affected many areas in many areas of the world including Lao PDR. SeThaMok sub-basin is a sub-basin that suffers from disasters as mentioned almost every year, especially in Phin district, which has caused enormous damage. Because of such a problem, it is necessary to assess the risk areas for floods and droughts in order to manage floods and droughts that are suitable for the area in order to move forward in planning to deal with floods and droughts in the future. Therefore, this study aims to study flood and drought risk areas as well as create flood maps in (2014, 2018, 2019) and drought maps in (2006, 2012, 2015) using ArcGIS 10.5. This study uses rainfall data from 4 stations using the Thiessen Polygon Method to calculate the average rainfall and using data from the survey, collecting actual data from the field together with the data collected by the Department of Natural Resources and Environment. The results of the study found that: in 2014, there was a flood area covering 11.93% of the total catchment area and the maximum flood level was about 26 meters compared to the lowest level of the catchment area. Among them, the flood event covered 20 villages; In 2018, there is a flood area covering 16.06% of the total catchment area and the maximum flood level is about 32 meters. Among them, the flood event covered 27 villages; In 2019, there is a flood area covering 20.91% and the maximum flood level is about 34 meters. Among them, the flood event covered 39 villages and the results of the evaluation of areas at risk of drought showed that: in 2007, there were areas at risk of drought covering 39.18% of the area of the SeThaMok sub-watershed which covered the number of villages around 32 villages; In 2012, there is a drought-prone area covering 43.29% of the SeThaMok sub-watershed area, which covers about 38 villages; In 2015, there is a drought-prone area covering 36.73% of the SeThaMok sub-basin area, which covers about 30 villages.

DPGS: Cross-cooperation guided dynamic points generation for scene text spotting

End-to-end text spotting aims to combine scene text detection and recognition into a unified framework. Dealing with the relationship between the two sub-tasks plays a pivotal role in designing effective spotters. While polygon or segmentation-based methods eliminate heuristic post-processing, they still face challenges such as background noise and high computational burden. In this study, we introduce DPGS, a coarse-to-fine learning framework that lets Dynamic Points Generation for text Spotting. DPGS simultaneously learns character representations for both detection and recognition tasks. Specifically, for each text instance, we represent the character sequence as ordered points and model them with learnable point queries. This approach progressively selects appropriate key points covering character and leverages group attention to associate similar information from different positions, improving detection accuracy. After passing through a single decoder, the point queries encode text semantics and locations, facilitating decoding to central line, boundary, script, and confidence of text through simple prediction heads. Additionally, we introduce an adaptive cooperative criterion to combine more useful feature knowledge, enhancing training efficiency. Extensive experiments show the superiority of our DPGS when handling scene text detection and recognition tasks. Compared to their respective top-1 methods, DPGS has significantly improved the average recognition accuracy by 3.7%, 1.9%, and 0.7% on the Total-Text, ICDAR15, and CTW1500 datasets, respectively.

Evaluation and Division Methods of Coupled Spatial Units between Parks and Living Circles: A Case Study of Four National-Level New Areas

This study, based on the perspective of supply and demand coupling between parks and living circles, divides spatial units by introducing the Thiessen polygon method with urban parks as the core. Simultaneously, the coefficient of variation (CV) was used to evaluate the distribution characteristics of these spatial units. The suitability of the spatial units was comprehensively evaluated through the three indicators of park service support, functional concentration of living circle, and management and development level. The Node–Place (NP) model was used to quantify the coupling relationship between the park and the living circle, and the characteristics of the coupling units were deeply analyzed from the aspects of supply and demand services, coupling configuration relationship, development management, etc. The results are empirically applied to four national-level new areas, thereby providing a new evaluation method and perspective for urban planning and management.

Koreksi Bias Data Hujan Satelit Persiann Sebagai Alternatif Pos Stasiun Hujan dengan Pendekatan Quantile Mapping di Sub Das Brantas Hulu

The rainfall data is usually obtained from meteorological stations, which many sill observed manually in Indonesia and can lead to an observation error. Remote sensing rainfall data observed by satellite offer interesting alternatives to overcome the limitation of existing meteorological stations in Indonesia. It offers accuracy, spatial coverage, timeliness and cost effectiveness. However it contains bias if compared to land based station. This research will evaluate rainfall data observed in PERSIANN (Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks) in Brantas Hulu Watershed. The rainfall data of 13 years from 12 stations is evaluated to obtain area averaged rainfall using Thiessen Polygon method. Three datasets from PERSIANN, PERSIANN CCS and PERSIANN CDR are compared statistically with the area averaged area for daily, monthly and yearly rainfall. Bias correction is performed using Quantile Mapping to match the cumulative distribution curve from the area averaged rainfall. Verification of bias correction is performed using 2 years data from 2019 to 2020. Finally, the extreme rainfall analysis is performed to test the corrected data for design rainfall calculations. The correlation of daily data shows poor agreement for all three datasets with correlation coefficient below 0,40. The monthly and yearly data gives better correlation with coefficient above 0,80. It shows that for time series event, the satellite data gives poor correlation with the area averaged rainfall. However, quantile mapping correction gives consistent cumulative distribution agreement for correction and model verification. The verification analysis shows an increase in coefficient correlation from 0.387 to 0.43 (daily) and 0.887 to 0.915 (monthly). In addition, there is a decrease in normalized root mean square error (NRMSE) from 31.03% to 16.91% (daily) and 46.03% to 14.03% (monthly). A decrease in normalized mean absolute error (NMAE) occurred from 16.12% to 9.74% (daily) and 31.67% to 10.07% (monthly). Beside that, the results of extreme rainfall analysis produce values that are very close to the rain station. So it is found that the PERSIANN CCS quantile mapping regression model is the best in improving data quality.

Analysis of Micro Hydro Potential as A New Renewable Energy Source

Electricity demand in Indonesia is currently increasing along with population growth, economic growth, and development. This increase can lead to an energy crisis if it is not accompanied by the provision of additional power plants. This study aims to analyze the micro-hydro potential located at Bangkong Waterfall, Kuningan Regency. The research uses a quantitative approach that begins with field surveys and data collection from relevant agencies. Next, the dependable discharge analysis uses the Thiessen polygon method based on rainfall data and watershed area, as well as flow discharge analysis using the rational method. The results of calculations using the Thiessen polygon method and the rational method yield Q80 with a minimum discharge of 0.009 m³/d and a maximum discharge of 1.160 m³/d. For direct discharge analysis, the Float method is used to calibrate the calculation results with field conditions. The direct discharge analysis using the Float method yields 0.32 m³/d. Based on the efficiency considerations of the micro-hydro power plant (MHPP) components such as a head of 20 meters, turbine type efficiency, water density, gravity factor, and flow discharge in the pipe of 0.109 m³/d, the potential power that can be generated at the Bangkong Waterfall micro-hydro power plant is 16,097.23 Watts or 16.097 Kilowatts.

Exploration of the Impact of Built Environment Factors on Morning and Evening Peak Ridership at Urban Rail Transit Stations: A Case Study of Changsha, China

<div>To identify the influences of various built environment factors on ridership at urban rail transit stations, a case study was conducted on the Changsha Metro. First, spatial and temporal distributions of the station-level AM peak and PM peak boarding ridership are analyzed. The Moran’s I test indicates that both of them show significant spatial correlations. Then, the pedestrian catchment area of each metro station is delineated using the Thiessen polygon method with an 800-m radius. The built environment factors within each pedestrian catchment area, involving population and employment, land use, accessibility, and station attributes, are collected. Finally, the mixed geographically weighted regression models are constructed to quantitatively identify the effects of these built environment factors on the AM and PM peak ridership, respectively. The estimation results indicate that population density and employment density have significant but opposite influences on the AM and PM peak ridership, which can be attributed to the opposite travel directions of commuters in the AM and PM peak. The recreational facility density, road density, and 10-min walking accessibility could significantly positively affect the PM peak ridership, and their influences vary greatly over space. Besides, the operating time of stations significantly positively affects both the AM and PM peak ridership, transfer stations have significantly larger PM peak ridership and terminal stations have significantly larger AM peak ridership. The findings are expected to provide new insights for agencies to formulate appropriate measures to improve the ridership of urban rail transit.</div>

Habitat use by a bird community in a Caatinga area: habitat seasonality and overlap

Habitat degradation is one of the main drivers of biodiversity loss, a phenomenon that significantly manifests in the Caatinga domain, where extensive habitat areas undergo modifications. Therefore, understanding how organisms select their habitats becomes crucial for effective conservation management. In this context, the present study aims to analyze habitat use, seasonality, and overlap within a bird community in an area located within the Caatinga domain, specifically at Fazenda Aba. Twelve monthly expeditions were conducted using the point-count method to estimate usage areas, habitat intensity, and overlap during both dry and rainy periods. Usage areas were measured using the Minimum Convex Polygon (MCP 100%) method, while the Kernel 95% estimator was employed to assess habitat intensity. Overlap was calculated using the Utilization Distribution Overlap Index (UDOI). The results revealed comprehensive use of the study area by the bird community, with more pronounced usage intensity in riparian forest environments. Additionally, an increase in usage areas was observed during the rainy period compared to the dry season, reflecting greater overlap during the scarcity season. It is suggested that riparian forest habitats play a fundamental role in maintaining avifauna, especially during droughts, promoting seasonal movements of species that tend to shift to areas with higher resource availability, resulting in convergence of utilized areas.

Creep deformation behavior and residual life prediction of low hardness P91 steel welded joints

The remaining creep life of the reheat section pipeline of low hardness P91 steel replaced in a certain power plant was studied. The rupture behavior of the joint was studied using metallographic microscope (OM), scanning electron microscope (SEM), and Electron Back Scatter Diffraction (EBSD), and the creep life was predicted. The results show that the rupture behavior of P91 steel and its joint during service is related to external stress. When the stress is high, the failure position of the joint is concentrated at the lowest hardness position, dominated by low strength martensitic deformation cracking; When the stress is low, the joint fails from FGHAZ in the form of Type IV cracking, resulting in a combination of martensitic structure degradation and pore nucleation. Type IV cracking has a significant impact on the life of joints, and the polygonal line OSD method based on fracture mode for life prediction can effectively improve the accuracy of material life prediction.

A deep learning approach to detection of oral cancer lesions from intra oral patient images: A preliminary retrospective study

IntroductionOral squamous cell carcinomas (OSCC) seen in the oral cavity are a category of diseases for which dentists may diagnose and even cure. This study evaluated the performance of diagnostic computer software developed to detect oral cancer lesions in intra-oral retrospective patient images. Materials and methodsOral cancer lesions were labeled with CranioCatch labeling program (CranioCatch, Eskişehir, Turkey) and polygonal type labeling method on a total of 65 anonymous retrospective intraoral patient images of oral mucosa that were diagnosed with oral cancer histopathologically by incisional biopsy from individuals in our clinic. All images have been rechecked and verified by experienced experts. This data set was divided into training (n = 53), validation (n = 6) and test (n = 6) sets. Artificial intelligence model was developed using YOLOv5 architecture, which is a deep learning approach. Model success was evaluated with confusion matrix. ResultsWhen the success rate in estimating the images reserved for the test not used in education was evaluated, the F1, sensitivity and precision results of the artificial intelligence model obtained using the YOLOv5 architecture were found to be 0.667, 0.667 and 0.667, respectively. ConclusionsOur study reveals that OCSCC lesions carry discriminative visual appearances, which can be identified by deep learning algorithm. Artificial intelligence shows promise in the prediagnosis of oral cancer lesions. The success rates will increase in the training models of the data set that will be formed with more images.