https://repositori.mypolycc.edu.my/jspui/handle/123456789/759 Thu, 22 Oct 2026 22:32:44 GMT 2026-10-22T22:32:44Z https://repositori.mypolycc.edu.my/jspui/handle/123456789/10937 Title: OPTIMIZATION OF EFFICIENCY PREDICTION PERFORMANCE FOR SPUN PILE USING HYBRID META-HEURISTIC MACHINE LEARNING ALGORITHMS Authors: Muhammad Nasim Bin Abdul Ghani, Abdul Ghani Abstract: Kajian ini mencadangkan satu rangka kerja pemodelan hibrid bagi meramalkan kecekapan cerucuk berputar dengan menggunakan algoritma pembelajaran mesin yang dioptimumkan melalui teknik metaheuristik berinspirasi semula jadi. Sebanyak 150 rekod ujian Pile Driving Analyzer (PDA) digunakan untuk membangunkan tiga model ramalan iaitu Adaptive Neuro-Fuzzy Inference System (ANFIS), Support Vector Machine (SVM), dan Regression Tree (RT). Setiap model mempunyai struktur fungsi yang berbeza, di mana ANFIS menggunakan fungsi keahlian berbentuk loceng umum, SVM menggunakan kernel fungsi asas radial Gaussian, dan RT menggunakan pembahagian binari berulang. Untuk meningkatkan prestasi model, hiperparameter telah dioptimumkan menggunakan algoritma Sparrow Search (SSA), Whale Optimization Algorithm (WOA), dan Manta Ray Foraging Optimization (MRFO). Penilaian prestasi menunjukkan bahawa model ANFIS yang dioptimumkan dengan SSA mencapai ketepatan tertinggi dengan RMX (RMSE = 0.123, R² = 1.000) dan FMX (RMSE = 0.560, R² = 1.000). Pengesahan telah dijalankan menggunakan data daripada bangunan lain dalam projek yang sama. Ramalan RMX menunjukkan perbezaan peratusan antara 0.0% hingga 3.7%, manakala FMX berada dalam lingkungan 0.1% hingga 6.4%, yang masih diterima untuk aplikasi praktikal. Keputusan ini membuktikan kebolehsesuaian model dalam persekitaran pembinaan yang serupa. Prototaip berasaskan MATLAB ini menawarkan alternatif yang boleh dipercayai dan menjimatkan kos berbanding kaedah ujian cerucuk konvensional dalam kejuruteraan geoteknik. This study proposes a hybrid modeling framework for predicting the efficiency of spun pile foundations by leveraging machine learning algorithms optimized through nature-inspired metaheuristic techniques. Utilizing a dataset comprising 150 Pile Driving Analyzer (PDA) test records, three predictive models were developed, namely Adaptive Neuro-Fuzzy Inference System (ANFIS), Support Vector Machine (SVM), and Regression Tree (RT). Each model incorporates distinct functional structures, with ANFIS using generalized bell-shaped membership functions, SVM employing a Gaussian radial basis function kernel, and RT utilizing recursive binary splitting. To enhance model performance, hyperparameters were optimized using the Sparrow Search Algorithm (SSA), Whale Optimization Algorithm (WOA), and Manta Ray Foraging Optimization (MRFO). Performance evaluation showed that the ANFIS model optimized by SSA achieved the highest predictive accuracy with RMX (RMSE = 0.123, R² = 1.000) and FMX (RMSE = 0.560, R² = 1.000). Validation was conducted using data from another building within the same project. The RMX predictions showed percentage differences ranging from 0.0% to 3.7%, indicating high reliability. For FMX, percentage differences ranged from 0.1% to 6.4%, within acceptable thresholds for practical application. These results demonstrate the model’s robustness in similar construction environments. The MATLAB-based prototype offers a reliable and cost-effective alternative to conventional pile testing methods in geotechnical engineering. Description: This research develops and optimizes hybrid machine learning models using metaheuristic algorithms to predict the efficiency of spun pile foundations. The study utilizes PDA test data and compares ANFIS, SVM, and regression tree models, each optimized with SSA, WOA, and MRFO, to improve predictive accuracy and practical application in geotechnical engineering. Sun, 01 Dec 2024 00:00:00 GMT https://repositori.mypolycc.edu.my/jspui/handle/123456789/10937 2024-12-01T00:00:00Z https://repositori.mypolycc.edu.my/jspui/handle/123456789/10133 Title: ZERO DISASTER APPLICATION Authors: IRFAN HAZIQ BIN A HALIM; MUHAMMAD AMIRUL AIMAN BIN YUSRI; KANAPATI A/L SARAVANAN; SYED MUHAMMAD FARHAN BIN SAYED AHMAD FAUZI Abstract: This report presents the development of a mobile application that aims to improve public reporting of natural disasters in the Kinta District is presented in this report. By providing real-time information about ongoing incidents, the app aims to empower residents to contribute to disaster response efforts. The improvement interaction included different stages as user requirements analysis, system design, implementation, and evaluation. The app has a dashboard with a lot of information about disasters, user registration and authentication, and an easy way to submit reports. Access to emergency services and resources, an interactive map, and real-time alerts and notifications were also integrated. The project also put a lot of emphasis on data analytics and visualization to find patterns and enhance strategies for disaster preparedness. Client criticism and testing assumed an important part in designing the application's functionalities and client experience. The Kinta District community's overall resilience and preparedness for natural disasters are bolstered by the project's outcomes. Laporan ini membentangkan pembangunan aplikasi mudah alih yang bertujuan menambah baik pelaporan awam tentang bencana alam di Daerah Kinta dibentangkan dalam laporan ini. Dengan menyediakan maklumat masa nyata tentang insiden yang sedang berlaku, aplikasi ini bertujuan untuk memperkasakan penduduk untuk menyumbang kepada usaha tindak balas bencana. Interaksi penambahbaikan termasuk peringkat yang berbeza seperti analisis keperluan pengguna, reka bentuk sistem, pelaksanaan dan penilaian. Apl ini mempunyai papan pemuka dengan banyak maklumat tentang bencana, pendaftaran dan pengesahan pengguna serta cara mudah untuk menyerahkan laporan. Akses kepada perkhidmatan dan sumber kecemasan, peta interaktif serta makluman dan pemberitahuan masa nyata turut disepadukan. Projek ini juga memberi banyak penekanan pada analisis data dan visualisasi untuk mencari corak dan meningkatkan strategi untuk kesiapsiagaan bencana. Kritikan dan ujian pelanggan mengambil bahagian penting dalam mereka bentuk fungsi aplikasi dan pengalaman pelanggan. Keseluruhan daya tahan dan kesiapsiagaan masyarakat Daerah Kinta menghadapi bencana alam didorong oleh hasil projek. Description: Kinta District, located in the state of Perak, Malaysia, is known for its rich cultural heritage, historical landmarks, and natural beauty. However, like many other regions around the world, natural disaster is still unavoidable in Kinta district. Over the years, the district has experienced various types of natural disasters that have had significant impacts on the local communities and the environment. One of the most common natural disasters in Kinta District is flooding. The district is prone to flooding due to its geographical location, which includes several rivers and water bodies. During the monsoon seasons or heavy rainfall, the rivers in the area can overflow, leading to widespread flooding in low-lying areas. These floods can cause damage to homes, infrastructure, and agricultural land, as well as disrupt transportation and daily activities of the residents. Another natural disaster that can affect Kinta District is landslides. The hilly terrain and steep slopes in some parts of the district make it susceptible to landslides, especially during periods of heavy rain or soil erosion. Landslides can pose a threat to residential areas located on or near slopes, leading to loss of lives and damage to properties. 2 In addition to flooding and landslides, Kinta District also experiences occasional occurrences of earthquakes. While these earthquakes are usually of low intensity, they can still cause some degree of damage to buildings and infrastructure, depending on their magnitude and proximity to populated areas. The impacts of natural disasters in Kinta District extend beyond physical damages. They can also lead to economic losses, displacement of communities, and disruption of essential services such as electricity, water supply, and communication networks. The local government, together with relevant agencies and organizations, work diligently to mitigate the risks and minimize the impacts of these natural disasters through early warning systems, disaster preparedness plans, and infrastructure improvements. By understanding the vulnerabilities and taking appropriate measures, the residents of Kinta District continue to adapt and build resilience in the face of natural disasters. Efforts in raising awareness, conducting emergency drills, and implementing sustainable land management practices are crucial for minimizing the adverse effects and ensuring the safety and well-being of the local population in the event of a natural disaster. Thu, 01 Jun 2023 00:00:00 GMT https://repositori.mypolycc.edu.my/jspui/handle/123456789/10133 2023-06-01T00:00:00Z https://repositori.mypolycc.edu.my/jspui/handle/123456789/2039 Title: APPLICATION DEVELOPMENT OF PREMIX CALCULATION AND PROGRESS TRACKING IN ROAD MAINTENANCE (PERIODIC PAVEMENT): ON- SITE CALCULATION PREMIX (OC Premix) Authors: AZIZAN, UMMI ATHIRAH Mon, 01 Jan 2024 00:00:00 GMT https://repositori.mypolycc.edu.my/jspui/handle/123456789/2039 2024-01-01T00:00:00Z https://repositori.mypolycc.edu.my/jspui/handle/123456789/2038 Title: FACTORS THAT CONTRIBUTE TOWARD ROLES OF INDUSTRIAL REVOLUTION TECHNOLOGIES IN CONSTRUCTION SAFETY Authors: SIMON, PAULUS ERNEST Mon, 01 Jan 2024 00:00:00 GMT https://repositori.mypolycc.edu.my/jspui/handle/123456789/2038 2024-01-01T00:00:00Z