Search Results - (( learning effectiveness moderating algorithm ) OR ( java implication based algorithm ))

Algorithms for moderating effect of emotional value from a cross-media data fusion perspective: a case study of Chinese dating reality shows by Zhang, Shasha, Dong, Qiming, Yasin, Megat Al Imran, Fang, Ng Chwee

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The implications for ahybrid detection technique against malicious sqlattacks on web applications by Bahjat Arif, Sarajaldeen Akram, Wani, Sharyar

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An intelligent risk management framework for monitoring vehicular engine health by Rahim, Md. Abdur, Rahman, Md. Arafatur, Rahman, Md. Mustafizur, Zaman, Nafees, Moustafa, Nour, Razzak, Imran

“…We created a decision model that used an infrastructure vulnerability assessment model and sensor-actuator data to diagnose and categorise engine conditions as good, minor, moderate, or critical. We used machine learning and deep learning algorithms to assess the effectiveness of the risk management system’s decision model. …”
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Benchmarking Robust Machine Learning Models Under Data Imperfections in Real-World Data Science Scenarios by Marlindawati, ., Mohammad, Azhar, Esha, Sabir

“…Multiple classical machine learning algorithms and deep learning models were assessed across diverse benchmark datasets. …”
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Digital Quran With Storage Optimization Through Duplication Handling And Compressed Sparse Matrix Method by Ashraf Saleh Mohammad Alomoush

Machine learning models for predicting the compressive strength of concrete with shredded pet bottles and m sand as fine aggregate by Nadimalla, Altamashuddinkhan, Masjuki, Siti Aliyyah, Gubbi, Abdullah, Khan, Anjum, Mokashi, Imran

“…Machine learning is a critical subset of AI that deliberates the development of self-trained algorithms that use previous databases and analysis for result predictions. …”
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Fuzzy Evaluation and Benchmarking Framework for Robust Machine Learning Model in Real-Time Autism Triage Applications by Shayea G.G., Zabil M.H.M., Albahri A.S., Joudar S.S., Hamid R.A., Albahri O.S., Alamoodi A.H., Zahid I.A., Sharaf I.M.

“…Our findings highlight the effectiveness of PCA algorithms, yielding 12 principal components with acceptable variance. …”

Investigating the relationship between the urban heat island effect and short-duration extreme rainfall in Kuala Lumpur by Tan, Yan Kai

“…LULC classification was performed using Support Vector Machine (SVM) and Random Forest (RF) algorithms, while LST was estimated using the Single Channel (SC) algorithm and surface urban heat island intensity (SUHII) was subsequently derived from the LST data. …”
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Modelling and investigating the impacts of climatic variables on ozone concentration in Malaysia using correlation analysis with random forest, decision tree regression, linear reg... by Balogun, A.-L., Tella, A.

“…These locations have high industries and are well urbanized. The four machine learning algorithms exhibit high predictive performances, generally ascertaining the predictive accuracy of the climatic variables. …”
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Modelling and investigating the impacts of climatic variables on ozone concentration in Malaysia using correlation analysis with random forest, decision tree regression, linear reg... by Balogun, A.-L., Tella, A.

“…These locations have high industries and are well urbanized. The four machine learning algorithms exhibit high predictive performances, generally ascertaining the predictive accuracy of the climatic variables. …”
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Surface water quality status and prediction during movement control operation order under COVID-19 pandemic: Case studies in Malaysia by Najah A., Teo F.Y., Chow M.F., Huang Y.F., Latif S.D., Abdullah S., Ismail M., El-Shafie A.

Unveiling sarcastic intent: web-based detection of sarcasm in news / Mohd Nazzim Lahaji, Tajul Rosli Razak and Mohammad Hafiz Ismail by Lahaji, Mohd Nazzim, Razak, Tajul Rosli, Ismail, Mohammad Hafiz

“…This study’s key novelty and contribution lie in addressing the domain-specific problem of sarcasm detection in news headlines, which has received limited attention in previous research. The proposed algorithm effectively distinguishes between sarcastic and non-sarcastic headlines by analysing the semantic features of words and the underlying attitude conveyed by the headline’s structure. …”
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Diabetic retinopathy detection using fusion of textural and optimized convolutional neural network features / Uzair Ishtiaq by Uzair , Ishtiaq

“…Combining Local Binary Patterns (LBP) based texture features and deep learning features resulted in the creation of the fused features vector which was then optimized using Binary Dragonfly Algorithm (BDA) and Sine Cosine Algorithm (SCA). …”
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Modified symbiotic organisms search optimization for automatic construction of convolutional neural network architectures by Jauro, Fatsuma, Abdullahi, Usman Ali, Abdulsalami, Aminu Onimisi, Ibrahim, Adamu Abubakar, Abdullahi, Mohammed, Chiroma, Haruna

“…The algorithm’s distinctive feature lies in its ability to perform non-numeric computations, rendering it adaptable to intricate deep learning problems. …”
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Development of Deep Learning Classification Model for Diabetic Retinopathy Detection and Grading by Nurul Mirza Afiqah, Tajudin

“…The rapid growth of technologies and AI has led to the development of Deep Learning (DL), in which its algorithms are stacked in a hierarchy of increasing complexity and abstraction. …”
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Operational structural damage identification using de-noised modal feature in machine learning / Chen Shilei by Chen , Shilei

“…By integrating ISMA, both supervised and unsupervised machine learning algorithms were investigated to develop real-time damage identification schemes. …”
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Predictive modeling of land surface temperature (LST) based on Landsat-8 satellite data and machine learning models for sustainable development by Pande C.B., Egbueri J.C., Costache R., Sidek L.M., Wang Q., Alshehri F., Din N.M., Gautam V.K., Chandra Pal S.

“…The ensemble framework combines three powerful machine learning algorithms: XG-Boost, Bagging-XG-Boost, and AdaBoost, to enhance the accuracy and robustness of LST predictions. …”

Classification of Mental Health Level of Students Using SMOTE and Soft Voting Ensemble Classifier and the DASS-21 Profile by Muhammad Imron, Rosadi, Khoirun, Nisa, Nanik, Kholifah

“…These findings support the use of ensemble learning and SMOTE for developing effective college student mental health screening systems, ultimately enabling timely intervention and support…”
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Diagnostic power of resting-state fMRI for detection of network connectivity in Alzheimer's disease and mild cognitive impairment: a systematic review by Ibrahim, Buhari, Suppiah, Subapriya, Ibrahim, Normala, Mohamad, Mazlyfarina, Abu Hassan, Hasyma, Syed Nasser, Nisha, Saripan, M. Iqbal

“…We conducted a systematic review aimed at determining the diagnostic power of rs-fMRI to identify FC abnormalities in the DMN of patients with AD or MCI compared with healthy controls (HCs) using machine learning (ML) methods. Multimodal support vector machine (SVM) algorithm was the commonest form of ML method utilized. …”
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Predictive modeling and feature attribution of CO₂ adsorption on LDH-derived materials using machine learning approach by Pinto, Mavin Jason, Sharath, S. S., Sudhakar, K., Priya, S. Shanmuga, Thirunavukkarasu, I.

“…Moderate calcination of the material emerges as the optimal synthesis window, which results in balanced porosity, structural stability, and basic site density. …”
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