{"id":26451045,"url":"https://github.com/llwusill/firepredictioncnn","last_synced_at":"2026-04-12T20:40:21.651Z","repository":{"id":282200352,"uuid":"947811803","full_name":"llwusill/FirePredictionCNN","owner":"llwusill","description":"CNN kullanarak Orman Yangını Tahmin/Tespit Sistemi","archived":false,"fork":false,"pushed_at":"2025-03-13T10:11:16.000Z","size":0,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-03-13T10:27:18.410Z","etag":null,"topics":["matplotlib","numpy","opencv-python","pandas","sckiit-learn","seaborn","tensorflow"],"latest_commit_sha":null,"homepage":"","language":"Jupyter Notebook","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/llwusill.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2025-03-13T09:36:50.000Z","updated_at":"2025-03-13T10:11:20.000Z","dependencies_parsed_at":"2025-03-13T10:37:26.005Z","dependency_job_id":null,"html_url":"https://github.com/llwusill/FirePredictionCNN","commit_stats":null,"previous_names":["llwusill/firepredictioncnn"],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/llwusill%2FFirePredictionCNN","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/llwusill%2FFirePredictionCNN/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/llwusill%2FFirePredictionCNN/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/llwusill%2FFirePredictionCNN/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/llwusill","download_url":"https://codeload.github.com/llwusill/FirePredictionCNN/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":244259968,"owners_count":20424649,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["matplotlib","numpy","opencv-python","pandas","sckiit-learn","seaborn","tensorflow"],"created_at":"2025-03-18T16:31:24.390Z","updated_at":"2026-04-12T20:40:21.604Z","avatar_url":"https://github.com/llwusill.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Fire Prediction using CNN \u0026 Machine Learning Models\n\nBu proje, **orman yangınlarını tespit etmek ve tahmin etmek** için **Convolutional Neural Networks (CNN)** ve geleneksel makine öğrenimi modellerini kullanmaktadır. Model, farklı algoritmalarla eğitilerek **en yüksek doğruluk oranına sahip olanın belirlenmesi** amaçlanmıştır.\n\n## Özellikler\n🔥 **Derin Öğrenme ile Görüntü Sınıflandırma** – CNN modeli kullanarak yangın tespiti.  \n🔥 **Makine Öğrenmesi Modelleri** – SVM, Naive Bayes ve Random Forest algoritmalarının karşılaştırılması.  \n🔥 **Veri Görselleştirme \u0026 Analiz** – Eğitim verileri görselleştirilerek analiz edilmiştir.  \n🔥 **Google Colab Uyumluluğu** – Google Drive entegrasyonu ile kolay kullanım.  \n\n## Modellerin Performans Karşılaştırması\n| Model | Doğruluk (%) |\n|--------|------------|\n| **SVM (Support Vector Machine)** | **94.12** |\n| **Random Forest** | 88.24 |\n| **Gaussian Naive Bayes** | 82.35 |\n\nSVM modeli en yüksek doğruluk oranına sahip olduğu için, **yangın tahmini için en iyi model** olarak belirlenmiştir.\n\n## Gereksinimler\nAşağıdaki kütüphanelerin yüklenmesi gerekmektedir:\n\n```bash\npip install tensorflow numpy pandas matplotlib seaborn scikit-learn opencv-python\n```\n\n## Nasıl Çalıştırılır?\n\n1️⃣ Google Colab veya Jupyter Notebook'ta açın\n\n2️⃣ Veri setini yükleyin\n\n3️⃣ Ön işleme adımlarını tamamlayın (görüntü temizleme, ölçekleme vb.)\n\n4️⃣ CNN ve diğer modelleri eğitin\n\n5️⃣ Sonuçları karşılaştırın ve en iyi modeli seçin\n\n## Data Set\n\nBu projede kullanılan dataseti boyutu sebebiyle proje bittikten sonra silmiştim. Aynı Data Set'i bulamasamda benzer bir Set'e aşağıdaki linkte bulabilirsiniz.\nhttps://www.kaggle.com/datasets/elmadafri/the-wildfire-dataset/data\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fllwusill%2Ffirepredictioncnn","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fllwusill%2Ffirepredictioncnn","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fllwusill%2Ffirepredictioncnn/lists"}