Version [1.3]- [pyrepo-mcda - Reference objects based MCDA software package] by Aleksandra Bączkiewicz, Jarosław Wątróbski, Kesra Nermend, Wojciech Sałabun

“…This paper presents the pyrepo-mcda Python package upgrade with the implementation of the Preference Vector Method (PVM) multi-criteria method. …”
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Intelligent Data Processing Methods for the Atypical Values Correction of Stock Quotes by T. V. Zolotova, D. A. Volkova

“…In general, the determination of outliers is subjective, and the decision is made individually for each specific dataset, considering its characteristics or existing experience in this area. …”
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Optimal Sizing of Hybrid Generation Systems (Photovoltaic System and Energy Storage System) for Off-Grid Applications by Jaime Guamangallo, Jefferson Porras, Carlos Quinatoa, Jimmy Vaca, Luis Chiza

“…To achieve this, the optimization problem is solved using the simplex method for linear programming, implemented through Python. The model considers test data on electrical energy demand and solar irradiation, alongside battery operating conditions such as state of charge (SOC) and upper and lower charge limits as key decision variables. …”
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Energy Consumption Analysis of Using Mashrabiya as a Retrofit Solution for a Residential Apartment in Al Ain Square, Al Ain, UAE by Lindita Bande, Anwar Ahmad, Saada Al Mansoori, Waleed Ahmed, Amna Shibeika, Shama Anbrine, Abdul Rauf

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SAR-driven flood inventory and multi-factor ensemble susceptibility modelling using machine learning frameworks by Krishnagopal Halder, Anitabha Ghosh, Amit Kumar Srivastava, Subodh Chandra Pal, Uday Chatterjee, Dipak Bisai, Frank Ewert, Thomas Gaiser, Abu Reza Md. Towfiqul Islam, Edris Alam, Md Kamrul Islam

“…The present research employed novel ML models—LR, SVM, RF, XGBoost, DNN, and Stacking Ensemble—developed in the Python environment and leveraged 18 flood-influencing factors to delineate flood-prone areas with precision. …”
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Observational study of ground-level ozone and climatic factors in Craiova, Romania, based on one-year high-resolution data by Hasan Yildizhan, Mihaela Tinca Udriștioiu, Tugce Pekdogan, Arman Ameen

“…Using two statistical analysis programs, Python and SPSS, a good understanding of the correlations between these variables and ozone concentration is obtained. …”
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Intelligent production adjustment early warning for shale gas wells based on fuzzy logic control by HE Chunyan, ZHAO Yong, LI Nanying, YANG Jian, CAO Haitao, TANG Ronglin

“…In the future, combining remote control of oil nozzles or choke valves to adjust the production regime can provide technical support for intelligent oil and gas fields.…”
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Supervised machine learning classification algorithms for detection of fracture location in dissimilar friction stir welded joints by Akshansh Mishra, Apoorv Vats

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Optimization Models for Reducing the Air Pollutants Emission in the Production of Insulation Bituminous by Faezeh Borhani, Majid Shafiepour Motlagh, Amir Houshang Ehsani, Yousef Rashidi, Alireza Noorpoor, Saeid Maddah

“…Finally, the proposed method can solve optimization problems and support environmental management decisions in the insulation industry.…”
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Power BI as an auxiliary tool for biostatistics by N. Yu. Dmitrieva

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Convolutional neural network for dog breed recognition system by К. Хотінь, В. Шимкович, П. Кравець, А. Новацький, Л. Шимкович

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Study on DEM Correction Method of Digital Twin Basic Data Baseboard by HONG Minghai, YAN Tao, LIU Hui, WANG Xingjian, JING Na, WANG Shiwei, WEI Wenjie, LI Xinan, FENG Chuqiao

“…DEM is one of the most important digital twin basic data and has played a huge role in water conservancy planning,design,and engineering construction.However,the existence of various DEM errors greatly reduces the credibility of analysis and application results.In particular,the missing value after terrain conversion to DEM greatly limits subsequent DEM-based analysis.Based on the principle of raster calculation,this paper calls the corresponding tool of ArcGIS by Python to correct the missing value at the overlapped area of a certain terrain converted to DEM by using the mean of eight valued pixels around the pixel.The results show that the calculation method is highly applicable,reliable,and fast.The data of the corrected and compared values of 306 NoData pixels in the study area are close to the 1∶1 line;the maximum difference between the corrected and compared values is only 3.55 m,and the medium error value is 0.75,which is far below the standard error limit.Calling Numpy through Python greatly improves the calculation speed (10 s),and ArcGIS currently has no tool for directly correcting this method.In contrast,the DEM correction method proposed in this paper can be processed in batch,without processing failures due to memory limit,which greatly improves the work efficiency and has a strong application value for processing digital twin basic data.…”
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Machine Learning with Evolutionary Parameter Tuning for Singing Registers Classification by Tales Boratto, Gabriel de Oliveira Costa, Alexsandro Meireles, Anna Klara Sá Teles Rocha Alves, Camila M. Saporetti, Matteo Bodini, Alexandre Cury, Leonardo Goliatt

“…To develop the present study, a dataset of 350 audio files encompassing the three aforementioned registers was constructed. Then, the TSFEL Python library was employed to extract 14 pieces of temporal information from the audio signals for subsequent classification by the employed ML models. …”
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‘Stratigraphically Homogeneous Zones’: automated construction and restitution procedure for engineering geology use by A. D’Agostino, A. Porchia, G. Tortorici, F. Pavano, G. Cavuoto, M. Moscatelli, G. Ortolano, S. Catalano

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Use of UAVs' multispectral images for sugar beet cultivars discrimination and yield estimation by Vasileios DRIMZAKAS–PAPADOPOULOS, Konstantinos NTOUROS, Constantine PAPATHEODOROU, Alexandros KONSTANTINIDIS

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A mobile application-based decision support system for routing and decision making problems by Oğuz Bedel, Fehmi Özsoydan, Kutay Çetinkurt, Metehan Bolat

“…In the present paper, a prototype of mobile application-based decision support system is developed for industrial systems including routing and multi-criteria decision making problems. …”
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A machine learning-based approach for constructing a 3D apparent geological model using multi-resistivity data by Jordi Mahardika Puntu, Ping-Yu Chang, Haiyina Hasbia Amania, Ding-Jiun Lin, M. Syahdan Akbar Suryantara, Jui-Pin Tsai, Hwa-Lung Yu, Liang-Cheng Chang, Jun-Ru Zeng, Lingerew Nebere Kassie

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Objective and Intelligent Acquisition of Two Types of Decision Data Based on Online Comment Information and Its Application in Emergency Decision-Making by Ruipu Tan, Lehua Yang, Jing Li

“…Abstract Given the urgent, dynamic, and uncertain nature of emergencies, the rapid response to emergencies and their control is challenging, with the intelligent, real-time acquisition of decision data being a key issue. However, most previous studies relied on simulations, experts, assumptions, questionnaires, and borrowed literature, which are impractical. …”
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Herramientas estadísticas avanzadas para el análisis de datos en investigaciones cuantitativas: Una revisión sistemática by Wilson Oswaldo Sánchez Macías, Jessica Marlene Anchundia, Wendy Isabel Montoya Arellano, Félix Jacinto García Córdova

“…Los resultados de la revisión revelan que las técnicas estadísticas avanzadas, como la regresión multivariada, el análisis de varianza y el análisis multivariado, son esenciales para mejorar la precisión de los estudios en áreas como la medicina, la educación y las ciencias sociales. …”
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Shape Penalized Decision Forests for Imbalanced Data Classification by Rahul Goswami, Aindrila Garai, Payel Sadhukhan, Palash Ghosh, Tanujit Chakraborty

“…Our method integrates a penalty on the surface-to-volume ratio of decision sets within decision tree construction, thereby inherently addressing class imbalance without additional sampling. …”
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