Search Results - (( pattern machine algorithm ) OR ( case research algorithm ))*

New bio-inspired barnacle optimizers based least-square support vector machine for time-series prediction of pandemic outbreaks by Marzia, Ahmed

“…Through real-world case studies and mathematical tests, GBO consistently outperforms alternative algorithms. …”
Get full text
Get full text

River flow prediction based on improved machine learning method: Cuckoo Search-Artificial Neural Network by Zanial W.N.C.W., Malek M.B.A., Reba M.N.M., Zaini N., Ahmed A.N., Sherif M., Elshafie A.

“…In this research, Artificial Neural Network (ANN) is integrated with a nature-inspired optimizer, namely Cuckoo search algorithm (CS-ANN). …”

Forecast innovative development level in green supply chains using a comprehensive fuzzy algorithm by Delgoshaei, Aidin, Beighizadeh, Razieh, Mohd Arffin, Mohd Khairol Anuar, Leman, Zulkiflle, Ali, Ahad

“…The outcomes demonstrate the superiority of the Support Vector Machine algorithm in terms of achieved maximum score and minimum error. …”
Get full text
Get full text

Evaluation of deep learning algorithm for inflow forecasting: a case study of Durian Tunggal Reservoir, Peninsular Malaysia by Latif S.D., Ahmed A.N., Sathiamurthy E., Huang Y.F., El-Shafie A.

Data mining for structural damage identification using hybrid artificial neural network based algorithm for beam and slab girder / Meisam Gordan by Meisam , Gordan

“…In the modeling phase, amongst all DM algorithms, the applicability of machine learning, artificial intelligence and statistical data mining techniques were examined using Support Vector Machine (SVM), Artificial Neural Network (ANN) and Classification and Regression Tree (CART) to detect the hidden patterns in vibration data. …”
Get full text
Get full text
Get full text

Optimal energy management strategies for hybrid electric vehicles : A recent survey of machine learning approaches by Jui, Julakha Jahan, Mohd Ashraf, Ahmad, Molla, Md Mamun, Muhammad Ikram, Mohd Rashid

“…We emphasize how machine learning algorithms may be adjusted to dynamic operating environments, how well they can identify intricate patterns in hybrid electric vehicle systems, and how well they can manage non-linear behaviors.…”
Get full text
Get full text
Get full text

Dynamic Mapping and Visualizing Dengue Incidences in Malaysia Using Machine Learning Techniques by Mathur, N., Asirvadam, V.S., Dass, S.C., Gill, B.S.

“…K-mean, KNN, and Expectation-Maximization (EM) algorithms are used to cluster the cases and visualize the pattern of dengue spread. …”
Get full text
Get full text

Employability prediction based on personality test using Naive Bayes Algorithm / Mohd Alief Mukhlis Mohd Adnin by Mohd Adnin, Mohd Alief Mukhlis

“…Moreover, there are some case of employees that quit their jobs due to depression and pressure at work. …”
Get full text
Get full text

Partitional clustering algorithms for highly similar and sparseness y-short tandem repeat data / Ali Seman by Seman, Ali

“…The idea was incorporated into a new algorithm called, k-Approximate Modal Haplotypes (&-AMH) algorithm. …”
Get full text
Get full text

Partitional clustering algorithms for highly similar and sparseness Y-Short Tandem Repeat Data / Ali Seman by Seman, Ali

Get full text
Get full text

Data Mining On Machine Breakdowns And Effectiveness Of Scheduled Maintenance by Tan, Su Sze

“…Last but not least, some of the complex data mining tasks are not able to perform because of the limited algorithms and machine learning in Orange software.…”
Get full text
Get full text

Characterization of Multiple Omics Signatures in Relation to Dietary Pattern for in Silico Personalised Colon Cancer Risk Stratification: Study Protocol for a Case-control Study an... by Nur Mahirah, Amani Mohammad, Mohd Razif, Shahril, Suzana, Shahar, Nor Fadilah, Rajab, Raja Affendi, Raja Ali *, Zairul Azwan, Mohd Azman, Syarul Nataqain, Baharum, Abrar Noor, Akramin Kamarudin, Chung, Felicia Fei Lei *, Razinah, Sharif

“…Multiple endpoints will be analyzed, namely metabolomic signatures, epigenetic marks, inflammatory markers and relationship with dietary patterns will be established. Multiple machine learning models will then be used to develop personalised risk stratification algorithms. …”
Get full text
Get full text

Biopattern: a biomimetic design framework for generating bio-inspired design (biomimicry) by Foo, Chin Thoong

“…The objective of this research is to develop a biomimetic design framework, BioPattern, which bridges this knowledge gap. …”
Get full text
Get full text
Get full text
Get full text

An algorithm for Elliott Waves pattern detection by Vantuch, T., Zelinka, I., Vasant, P.

“…The Random Decision Forest and the Support Vector Machine are the machine learning algorithms employed for this task. …”
Get full text
Get full text

An algorithm for Elliott Waves pattern detection by Vantuch, T., Zelinka, I., Vasant, P.

“…The Random Decision Forest and the Support Vector Machine are the machine learning algorithms employed for this task. …”
Get full text
Get full text

Modified word representation vector based scalar weight for contextual text classification by Abbas Saliimi, Lokman

“…To bridge this gap, a five-phase research methodology is structured to propose and evaluate an algorithm enabling the external modification of LLM-generated word vectors using scalar values as the focus weightage. …”
Get full text
Get full text

Geospatial AI-based approach to assess the spatiotemporal suitability of onshore wind-solar farms in Iraq by Sachit, Mourtadha Sarhan Almushattat

“…In this context, global geospatial data for 13 conditioning factors were collected, and 55,619 inventory samples of wind and solar stations worldwide were prepared to train three machine learning (ML) algorithms, namely Random Forest (RF), Support Vector Machine (SVM), and Multi-Layer Perceptron (MLP). …”
Get full text
Get full text
Get full text

Financial time series predicting using machine learning algorithms by Tiong, Leslie Ching Ow *

“…Thereafter, Artificial Neural Network (ANN) and Support Vector Machine (SVM) algorithms are implemented separately to train with the trend patterns for predicting the movement direction of financial trends. …”
Get full text

Exploring students' performance in mathematics in Portugal using data analytics techniques: a data science use-case by Hassan, Raini, Fadzleey, Nur Zulfah Insyirah, Ab Hamid, Annesa Maisarah, Abd Aziz, Rabiatul Adawiyah, Jamalullain, Afiefah, Syaiful 'Adli, Fatin Syafiqah

“…The purpose is to identify the key factors influencing academic performance, providing insights for targeted interventions and support systems. Machine learning algorithms, specifically Random Forest Regression and Decision Trees, are utilized to analyze the dataset and determine the most significant factor impacting student performance. …”
Get full text
Get full text
Get full text

Twofold Integer Programming Model for Improving Rough Set Classification Accuracy in Data Mining. by Saeed, Walid

“…The accuracy for rules and classification resulted from the TIP method are compared with other methods such as Standard Integer Programming (SIP) and Decision Related Integer Programming (DRIP) from Rough Set, Genetic Algorithm (GA), Johnson reducer, HoltelR method, Multiple Regression (MR), Neural Network (NN), Induction of Decision Tree Algorithm (ID3) and Base Learning Algorithm (C4.5); all other classifiers that are mostly used in the classification tasks. …”
Get full text
Get full text