A new method for determining factors Influencing productivity of deep coalbed methane vertical cluster wells by HUANG Li, XIONG Xianyue, WANG Feng, SUN Xiongwei, ZHANG Yixin, ZHAO Longmei, SHI Shi, ZHANG Wen, ZHAO Haoyang, JI Liang, DENG Lin

Get full text

Leveraging Machine Learning for Accurate and Fast Stellar Mass Estimation of Galaxies by Vahid Asadi, Akram Hasani Zonoozi, Hosein Haghi, Fatemeh Abedini, Atousa Kalantari, Marziye Jafariyazani, Nima Chartab

Get full text

Applications of Multi-Robotic Arms to Assist Agricultural Production: A Review by Xiaojian Gai, Chang Xu, Yajia Liu, Qingchun Feng, Shubo Wang

“…This paper summarizes the key technologies used in current research, including heuristic algorithms, fast search rapidly exploring random trees, reinforcement learning algorithms, etc., and focuses on reviewing the present applications of cutting-edge reinforcement learning algorithms in agricultural robotic arms. …”
Get full text

Fast and Efficient Drone Path Planning Using Riemannian Manifold in Indoor Environment by Rohit Dujari, Brijesh Patel, Bhumeshwar K. Patle

Get full text

Predicting climate-driven shift of the East Mediterranean endemic Cynara cornigera Lindl by Heba Bedair, Heba Bedair, Yehia Hazzazi, Asmaa Abo Hatab, Marwa Waseem A. Halmy, Mohammed A. Dakhil, Mohammed A. Dakhil, Mubaraka S. Alghariani, Mubaraka S. Alghariani, Mari Sumayli, A. El-Shabasy, Mohamed M. El-Khalafy

Get full text

Spatiotemporal heterogeneity of the ecological civilization in the Yangtze River economic belt by Li Ma, Huiyuan Zhang, Xiaojie Meng, Qing Lu

Get full text

Efficient Machine Learning Model for DDoS Detection System Based on Dimensionality Reduction by Saad Ahmed Dheyab, Shaymaa Mohammed Abdulameer, Salama Mostafa

“…Subsequently, DDoS attack detection is performed based on random forest (RF) and decision tree (DT) algorithms. …”
Get full text

COMPARATIVE ANALYSIS OF COLORING ALGORITHMS FOR ORDINARY WEIGHTED GRAPH by Andrey Sergeyevich Merzlenko, Valery Grigoryevich Kobak

Get full text

Hybrid Weighted Random Forests Method for Prediction & Classification of Online Buying Customers by Umesh Kumar Lilhore, Sarita Simaiya, Devendra Prasad, Deepak Kumar Verma

“…This research article mainly proposed an extension of the Random Forest classifier named “Weighted Random Forests” (wRF), which incorporates tree-level weights to provide much more accurate trees throughout the calculation as well as an assessment of vector relevance. …”
Get full text

Computerised analysis of non-conjugate spiral bevel gear mesh using an advanced and fast-converging tooth contact model by Maksat Temirkhan, Andas Amrin

Get full text

An exploratory study of high-educated poverty through machine learning approach: a case study of East Java, Indonesia by Dias Satria, Risti Permani, Kodrad Winarno, David Kaluge, Citra Rahayu Indraswari, Radityo Putro Handrito

Get full text

Comparative analysis of machine learning algorithms for predicting depression among individuals with diabetes by Hind Bourkhime, Noura Qarmiche, Soumaya Benmaamar, Nada Lazar, Mohammed Omari, Mohamed Berraho, Nabil Tachfouti, Samira El Fakir, Hanan El Ouahabi, Nada Otmani

Get full text

In-Memory Versus Disk-Based Computing with Random Forest for Stock Analysis: A Comparative Study by Chitra Joshi, Chitrakant Banchorr, Omkaresh Kulkarni, Kirti Wanjale

Get full text

Introducing Primality Testing Algorithm with an Implementation on 64 bits RSA Encryption Using Verilog by Rehan Shams, Fozia Hanif Khan, Umair Jillani, M. Umair

Get full text

Genotyping Identification of Maize Based on Three-Dimensional Structural Phenotyping and Gaussian Fuzzy Clustering by Bo Xu, Chunjiang Zhao, Guijun Yang, Yuan Zhang, Changbin Liu, Haikuan Feng, Xiaodong Yang, Hao Yang

“…Subsequently, we harnessed the TreeQSM algorithm, which is custom-designed for extracting tree topological structures, to extract 11 archetypal structural phenotypic parameters of the maize tassels. …”
Get full text

Tree-Based Algorithms and Incremental Feature Optimization for Fault Detection and Diagnosis in Photovoltaic Systems by Khaled Chahine

Get full text

Prediction of Optimum Operating Parameters to Enhance the Performance of PEMFC Using Machine Learning Algorithms by Arunadevi M, Karthikeyan B, Anirudh Shrihari, Saravanan S, Sundararaju K, R Palanisamy, Mohamed Awad, Mohamed Metwally Mahmoud, Daniel Eutyche Mbadjoun Wapet, Abdulrahman Al Ayidh, Hany S. Hussein, Mahmoud M. Hussein, Ahmed I. Omar

“…Different MLAs are modelled to explore the PEMFC performance and results proved that gradient boosting regression provides better predictions compared to other algorithms such as decision tree regressor, support vector machine regressor, and random forest regression.…”
Get full text

Leveraging mixed-effects regression trees for the analysis of high-dimensional longitudinal data to identify the low and high-risk subgroups: simulation study with application to g... by Mina Jahangiri, Anoshirvan Kazemnejad, Keith S. Goldfeld, Maryam S. Daneshpour, Mehdi Momen, Shayan Mostafaei, Davood Khalili, Mahdi Akbarzadeh

“…Previous studies have shown that this model can be sensitive to parametric assumptions and provides less predictive performance than non-parametric methods such as random effects-expectation maximization (RE-EM) and unbiased RE-EM regression tree algorithms. …”
Get full text

Model Klasifikasi Machine Learning untuk Prediksi Ketepatan Penempatan Karir by Hendri Mahmud Nawawi, Agung Baitul Hikmah, Ali Mustopa, Ganda Wijaya

“…The complexity of the job market requires individuals and organizations to understand the trends and needs of the world of work. One of the main challenges is the right career placement. That is becoming increasingly popular is the use of Machine Learning  algorithms in the decision-making process. …”
Get full text

Dye-cleaning prediction with a variant of nature-inspired algorithms coupled with extreme gradient boosting by Tiyasha Tiyasha, Chijioke Elijah Onu, Mohamed A. Ismail, Rama Rao Karri, Abdelfattah Amari, Vinay Kumar, Suraj Kumar Bhagat

“…Hyperparameter tuning via differential evolution (DE), genetic algorithm (GA), random search (RS), and grid search (GS) with the XGBoost model was conducted to achieve more accurate results. …”
Get full text