Ain Shams Engineering Journal最新文献

{"title":"First-principles study of Cs2AgXBr6 (X = In, Bi): A hierarchy of functional performance for renewable energy applications","authors":"Ghiyas Anwar ,&nbsp;Zafar Iqbal ,&nbsp;Muhammad Majid Gulzar ,&nbsp;Ali Arishi","doi":"10.1016/j.asej.2025.103537","DOIUrl":"10.1016/j.asej.2025.103537","url":null,"abstract":"<div><div>In recent years, lead-free double halide perovskites have attracted significant attention due to their potential in renewable energy technologies. To explore their suitability for eco-friendly applications, we have investigated the structural, elastic, electronic, optical, and photocatalytic properties of Cs₂AgXBr₆ (X = In, Bi) double perovskites. These characteristics were calculated using the WIEN2k code with the full-potential linearized augmented plane-wave (FP-LAPW) method based on density functional theory (DFT). Using the strongly constrained and appropriately normed (SCAN) meta-GGA functional, we calculated lattice constants of 11.0501 Å and 11.2998 Å and band gaps of 0.208 eV and 1.277 eV for Cs₂AgInBr₆ and Cs₂AgBiBr₆, respectively. By joining the Tran–Blaha modified Becke–Johnson (TB-mBJ) potential with the SCAN functional, we obtained improved band gap values of 1.796 eV (X = In) and 2.304 eV (X = Bi), showing better agreement with experimental data. The structural stability of both compounds is evaluated using modified Goldschmidt and octahedral tolerance factors. The elastic constants, obtained using the SCAN functional, suggest that the materials are mechanically stable and ductile. Both functionals are employed to study optical properties by calculating relevant optical parameters such as absorption coefficient, <span><math><mrow><mi>α</mi><mfenced><mrow><mi>ω</mi></mrow></mfenced><mo>,</mo></mrow></math></span> energy loss function, <span><math><mrow><mi>L</mi><mfenced><mrow><mi>ω</mi></mrow></mfenced></mrow></math></span>, extinction coefficient,<span><math><mrow><mi>k</mi><mfenced><mrow><mi>ω</mi></mrow></mfenced></mrow></math></span>, and optical conductivity, <span><math><mrow><mi>σ</mi><mfenced><mrow><mi>ω</mi></mrow></mfenced></mrow></math></span>. Subsequently, the potential of these materials for photocatalytic hydrogen production via overall water splitting is systematically examined. Our study demonstrates that the SCAN and TB-mBJ functionals offer reliable results while significantly reducing computational cost compared to resource-intensive hybrid DFT methods.</div></div>","PeriodicalId":48648,"journal":{"name":"Ain Shams Engineering Journal","volume":"16 9","pages":"Article 103537"},"PeriodicalIF":6.0,"publicationDate":"2025-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144307938","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Explainable AI-driven evaluation of plant protein rheology using tree-based and Gaussian process machine learning models","authors":"Mustafa Tahsin Yilmaz ,&nbsp;Salman Badurayq ,&nbsp;Kemal Polat ,&nbsp;Ahmad H. Milyani ,&nbsp;Abdulaziz S. Alkabaa ,&nbsp;Osman Gul ,&nbsp;Furkan Turker Saricaoglu","doi":"10.1016/j.asej.2025.103565","DOIUrl":"10.1016/j.asej.2025.103565","url":null,"abstract":"<div><div>In this study, we conducted a comparative analysis of the explainability of Decision Tree Regressor (DTR) and Gaussian Process Regressor (GPR) models in predicting the shear stress and viscosity of sesame protein isolate (SPI) systems, employing explainable machine learning (EML) techniques to elucidate complex, nonlinear relationships among processing parameters. SPI samples were processed across pressure levels ranging from 0 to 100 MPa and ion concentration (IC) values from 0 to 200 mM. DTR model accurately predicted shear stress (<em>R</em>² = 0.999), while a GPR model achieved high performance for viscosity prediction (<em>R</em>² = 0.9925). Formally, the modeling task is framed as learning a predicting mapping function <span><math><mrow><mi>f</mi><mo>:</mo><msup><mrow><mi>R</mi></mrow><mi>p</mi></msup><mo>→</mo><mi>R</mi></mrow></math></span>, where <span><math><mrow><mi>x</mi><mo>∈</mo><msup><mrow><mi>R</mi></mrow><mi>p</mi></msup></mrow></math></span> denotes the vector of predictors (pressure, IC, shear rate) and <span><math><mrow><mi>y</mi><mo>∈</mo><mi>R</mi></mrow></math></span> is the target variable (shear stress or viscosity), by minimizing a loss function such as mean squared error. Interpretation of model predictions using SHapley Additive exPlanations (SHAP), permutation importance, and partial dependence analysis revealed that pressure and IC are the most influential factors affecting shear stress and viscosity, with pressure inducing protein conformational changes that impact rheological properties. The shear rate exhibited a lesser direct impact within the systems examined. Partial Dependence Plots (PDPs) from the DTR model revealed strong, nearly linear positive relationships between pressure and shear stress, while the GPR model depicted more nuanced responses, highlighting the models’ differing sensitivities. Variance-Based Sensitivity Indices (VBSIs) further quantified these influences, with pressure and IC showing higher sensitivity scores in the DTR model compared to the GPR model. Permutation importance and SHAP interaction analyses corroborated these results, emphasizing the dominant role of pressure and IC, both independently and interactively, in determining shear stress. In contrast, viscosity predictions were influenced by more distributed and subtle interactions among all features. Employing explainable machine learning techniques enables a comprehensive understanding of feature relevance in complex, nonlinear rheological systems, facilitating the elucidation of viscosity development in sesame protein systems through rheological indices. This approach ensures no bias toward formulation composition and applied pressure, offering valuable insights for optimizing formulation and processing conditions in food applications to enhance the functional properties of SPI-based products.</div></div>","PeriodicalId":48648,"journal":{"name":"Ain Shams Engineering Journal","volume":"16 9","pages":"Article 103565"},"PeriodicalIF":6.0,"publicationDate":"2025-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144307939","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Experimental investigations of strengthened beam with co-cured carbon FRP and mussel shell-modified epoxy","authors":"Syahrin Azhar ,&nbsp;Sugiman Sugiman ,&nbsp;Zaim Omar ,&nbsp;Hilton Ahmad","doi":"10.1016/j.asej.2025.103563","DOIUrl":"10.1016/j.asej.2025.103563","url":null,"abstract":"<div><div>Traditional strengthening materials, such as carbon fibre reinforced polymer (CFRP) plates bonded with synthetic fillers, often rely on non-renewable resources and may have limited environmental compatibility. Thus, mussel shells with a high content of calcium carbonate particles act as rigid particles and alternatives to synthetic filler counterparts added in epoxy resin, enhancing the mechanical properties of filled epoxy. This paper aims to investigate the improvement of flexural resistance by incorporating mussel shell powder as a bio-filler of epoxy resin (hereafter referred to as mussel shell-modified epoxy, MME), which was then used as the bonding agents with CFRP sheets via co-cured technique as a beam strengthening method. A four-point bending test was conducted to investigate four parametric studies, i.e., CFRP bonded lengths (Series A), mussel shell powder volume fraction (Series B) and different percentages of pre-load applied on concrete beams with different bonding agent types, i.e., MME (Series C) and neat epoxy resin (Series D). A 7.5% volume fraction of MME and the most extended CFRP sheet enhanced the ultimate load with deflection (associated with concrete ductility) of the strengthened plain beams by 108% and 58%, respectively, compared to the control beam. Interestingly, up to 66% improvement was observed in Series C by applying pre-load at 60% of the control beam’s ultimate load, comparing beams strengthened with MME to those using neat epoxy (Series D). In this test, pre-loading was applied by subjecting the concrete beams to 60% of their ultimate capacity using a Universal Testing Machine (UTM) before applying CFRP sheets, ensuring consistent initial stress conditions for reliable comparison. Hence, MME is a viable bio-filler incorporated in epoxy resin to enhance co-cured CFRP as a strengthening material.</div></div>","PeriodicalId":48648,"journal":{"name":"Ain Shams Engineering Journal","volume":"16 10","pages":"Article 103563"},"PeriodicalIF":6.0,"publicationDate":"2025-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144307453","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Understanding chemical ecotoxicity through interpretable ensemble learning","authors":"Manish Kumar Tripathi ,&nbsp;Sneha Pandey ,&nbsp;Anoop Kumar Tiwari ,&nbsp;Kottakkaran Sooppy Nisar ,&nbsp;Abhigyan Nath","doi":"10.1016/j.asej.2025.103574","DOIUrl":"10.1016/j.asej.2025.103574","url":null,"abstract":"<div><div>Characterization factors are used in life cycle assessments to translate the quantity of chemicals and other pollutants produced during a product’s life cycle into the standard unit of an impact category, such as ecotoxicity. The chemical ecotoxicity (HC50) evaluation is an expedient method to determine the harmful effects of these chemicals on ecosystems. Ecotoxicity parameters for a wide variety of compounds are therefore a genuine and significant concern. The current work employed an optimized XGBoost model for real value prediction of HC50 values. Further the optimized prediction model is analysed using a series of model agnostic explainable learning approaches. The best optimized model achieved an acceptable R² = 0.684 with mse = 0.587. Further, the best optimized model is subjected to various global and local explainable algorithms, resulting in turning the black box model into a white box model, resulting in interpretation of how the decisions are being made by the learned model.</div></div>","PeriodicalId":48648,"journal":{"name":"Ain Shams Engineering Journal","volume":"16 9","pages":"Article 103574"},"PeriodicalIF":6.0,"publicationDate":"2025-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144307940","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Weddle's inequalities in fractional space","authors":"Qi Liu ,&nbsp;Muhammad Zakria Javed ,&nbsp;Muhammad Uzair Awan ,&nbsp;Yuanheng Wang ,&nbsp;Ahmed M. Zidan","doi":"10.1016/j.asej.2025.103550","DOIUrl":"10.1016/j.asej.2025.103550","url":null,"abstract":"<div><div>The literature clearly demonstrates the investigation of various approaches, including Newton–Cotes procedures, to approximate the integrals with high accuracy. A closed method based on seven points that approximates the quantities by a sixth-degree polynomial is known as Weddle's rule. This study assesses the error analysis of this renowned procedure to seek out the shortcomings of classic error inequality to produce new bounds for a larger space of functions within the fractional calculus. A new Riemann-Liouville fractional identity for differentiable functions is developed. To construct various estimates of Weddle's inequality, we utilize this identity together with properties of several benchmark functions like convex, Lipschitz, and bounded variation functions. Graphical and numerical comparisons are supplied to justify the obtained results. Lastly, we present the applicable analysis of primary findings to the theory of means, composite error bounds, and particularly a bi-quadratic iterative method is developed.</div></div>","PeriodicalId":48648,"journal":{"name":"Ain Shams Engineering Journal","volume":"16 10","pages":"Article 103550"},"PeriodicalIF":6.0,"publicationDate":"2025-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144296827","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Energy-aware data sharing protocol for vision disability management","authors":"Mohammad Zubair Khan ,&nbsp;Ahmad Naseem Alvi ,&nbsp;Haider Ali ,&nbsp;Muhammad Awais Javed ,&nbsp;Mohammad Mahyoob Albuhairy ,&nbsp;Jeehaan Algaraady ,&nbsp;Nadim Rana","doi":"10.1016/j.asej.2025.103547","DOIUrl":"10.1016/j.asej.2025.103547","url":null,"abstract":"<div><div>The Internet of Medical Things (IoMT) is an emerging and impactful research area in healthcare, focused on enabling seamless data exchange among medical devices and sensors to enhance patient care and lifestyle. One promising application of IoMT is integrative medical imaging, where data from various imaging devices are shared with a central server to facilitate accurate diagnostics and prevent potential disabilities. IoMT also plays a critical role in managing vision-related impairments, such as monitoring patients' walking patterns to prevent falls and injuries. Timely intervention is essential for patients at risk of falling, necessitating continuous online monitoring of their vital signs.</div><div>To support this, various wireless sensors are deployed on patients to track their health conditions and mobility. These sensors typically operate with limited energy reserves and are often designed to harvest energy from their environment to extend their operational lifetime. However, during emergencies, the demand for data transmission surges, leading to rapid energy depletion. To ensure energy efficiency and reliable communication, it is crucial to avoid data collisions. Therefore, contention-free Medium Access Control (MAC) protocols like Time Division Multiple Access (TDMA) are preferred over contention-based alternatives.</div><div>This work proposes a TDMA-based MAC protocol, referred to as TMPH (TDMA-based MAC Protocol for Health monitoring), aimed at facilitating efficient transmission of health and imaging-related data. TMPH integrates the Technique for Order of Preference by Similarity to the Ideal Solution (TOPSIS), a multi-criteria decision-making approach, to optimize transmission rates, maximize link utilization, and prolong the lifecycle of wireless sensor nodes in response to varying data traffic demands. The proposed protocol is evaluated against traditional First Come First Serve (FCFS) and Shortest Job First (SJF)-based BS-MAC protocols. Simulation results demonstrate that TMPH significantly enhances data transmission performance, improves link utilization, and extends the network's operational life.</div></div>","PeriodicalId":48648,"journal":{"name":"Ain Shams Engineering Journal","volume":"16 10","pages":"Article 103547"},"PeriodicalIF":6.0,"publicationDate":"2025-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144296826","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Beyond conventional modeling: A cutting-edge hybrid IAER-AMT decision-tree-based algorithm for high-resolution river turbidity prediction","authors":"Khabat Khosravi ,&nbsp;Aitazaz Ahsan Faroouqe ,&nbsp;Ali Reza Shahvaran ,&nbsp;Prasad Daggupati ,&nbsp;Salim Heddam ,&nbsp;Javad Hatamiafkoueieh","doi":"10.1016/j.asej.2025.103511","DOIUrl":"10.1016/j.asej.2025.103511","url":null,"abstract":"<div><div>Water Turbidity (TU) is a widely used indicator of water quality. Given the time-consuming nature of direct TU measurement, developing an accurate predictive model is imperative. In this study, the alternating model tree (AMT) and its ensemble version through iterative absolute error regression (IAER), bootstrap aggregating (BA), weighted instance handler wrapper (WIHW), and random subspace (RS) were used to predict TU at Clackamas River, USA. Daily time-series data of the physicochemical water quality variables from 2006 to 2023, including water temperature (Tw), specific conductance (SC), dissolved oxygen (DO), pH, as well as physical river parameters, including daily water discharge (Q) and water stage (WS), were used as potential input variables to predict TU. The manual approach, principal component analysis (PCA), and correlation-based feature selection subset evaluation (CfsSubsetEval) techniques were compared under different input scenarios. Finally, the performance of the models was evaluated using various statistical metrics, including the coefficient of determination (R²), root mean squared error (RMSE), percentage of bias (PBIAS), Nash-Sutcliffe efficiency (NSE), and root mean standard deviation ratio (RSR). WS had the highest impact on TU prediction, whereas Tw was less correlated. In addition, the input scenario that included all variables led to the highest model performance. Based on the testing dataset, the novel IAER-AMT hybrid algorithm outperformed others, achieving an RMSE of 1.20 Formazin Nephelometric Units (FNU), an NSE of 0.72, a PBIAS of 3.17 %, and an RSR of 0.53 followed by BA-AMT (RMSE = 1.30 FNU, NSE = 0.67, PBIAS =  −9.73%, and RSR = 0.57), WIHW-AMT (RMSE = 1.34 FNU, NSE = 0.65, PBIAS =  −0.35%, RSR = 0.58), RS-AMT (RMSE = 1.37 FNU, NSE = 0.64, PBIAS =  −20.95%, and RSR = 0.60), and AMT (RMSE = 1.38 FNU, NSE = 0.63, PBIAS =  −26.81%, and RSR = 0.60).</div></div>","PeriodicalId":48648,"journal":{"name":"Ain Shams Engineering Journal","volume":"16 9","pages":"Article 103511"},"PeriodicalIF":6.0,"publicationDate":"2025-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144297374","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Least-square-based transform methods for analytical solutions of fractional-order nonlinear (1+1)-dimensional dynamics equations","authors":"Naveed Iqbal ,&nbsp;Meshari Alesemi","doi":"10.1016/j.asej.2025.103535","DOIUrl":"10.1016/j.asej.2025.103535","url":null,"abstract":"<div><div>In this work, we consider the analysis of the nonlinear Burgers' equation as a fractional-order partial differential equation using the Caputo derivation. Two new, effective methods, the least-square residual power series transform method and the least-square variational iteration transform method, are introduced to deal with the fractional Burgers' equation. These techniques combine the merits of least-square approximation, residual power series, variational iteration, and integral transformations to obtain accurate and convergent solutions. The Caputo derivative describes the fractional-order dynamics, which provides the best robustness and accuracy to explain complex physical processes. The proposed schemes are systematically implemented for Burgers' equation with a nonlinear source and their performances are illustrated by a comprehensive comparison and numerical process. The results highlight the precision, efficiency, and reliability of the least-square residual power series transform method and least-square variational iteration transform method methods in the solution of fractional-order complex space partial differential equations and show that the least-square residual power series transform method and least-square variational iteration transform method are dependable methods for researchers and engineers in the field of applied mathematics and mathematical physics. This work has made an essential contribution to the relatively new field of fractional calculus and provides a powerful tool for solving other non-linear fractional differential equations in science and engineering.</div></div>","PeriodicalId":48648,"journal":{"name":"Ain Shams Engineering Journal","volume":"16 9","pages":"Article 103535"},"PeriodicalIF":6.0,"publicationDate":"2025-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144291463","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Barrier function-based adaptive synergetic control with state constraints for manipulator with uncertainty and input saturation","authors":"Muhammad Auzan ,&nbsp;Yong-Lin Kuo","doi":"10.1016/j.asej.2025.103555","DOIUrl":"10.1016/j.asej.2025.103555","url":null,"abstract":"<div><div>This study proposes a barrier function-based adaptive nonsingular terminal synergetic control to mitigate chattering and uncertainty in a nonlinear system with hard state constraints and actuator saturation. The controller addresses the uncertainty by utilizing a barrier function-based evolution constraint. Furthermore, the controller incorporates a barrier function-based macrovariable to modify the control behavior and constrain the system states within predefined ranges. The design is presented for an n-th-order nonlinear system, and the stability is proven using the Lyapunov stability theorem. Simulation with constant reference demonstrates the effectiveness of the proposed controller in constraining the system states, and experiments with impulse, sine, and bounded random uncertainty illustrate the controller's ability to handle uncertainty without explicitly defining the worst-case assumption. Moreover, implementation on a robotic manipulator demonstrates the advantage of the proposed method compared to four adaptive controllers in terms of continuous control law, chattering-free response, simplicity in tuning parameters, and tracking performance.</div></div>","PeriodicalId":48648,"journal":{"name":"Ain Shams Engineering Journal","volume":"16 9","pages":"Article 103555"},"PeriodicalIF":6.0,"publicationDate":"2025-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144291437","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Enhancing multi-criteria decision-making through a novel feedforward neural network system based on group experience","authors":"Hsiang-Yu Chung ,&nbsp;Jen-Chieh Chang ,&nbsp;Kuei-Hu Chang","doi":"10.1016/j.asej.2025.103552","DOIUrl":"10.1016/j.asej.2025.103552","url":null,"abstract":"<div><div>In recent years, artificial intelligence (AI) has developed rapidly by leveraging the collective group experience derived from big data. This has led to continuous refinement of feasible solutions to various evaluation criteria within databases, thereby identifying alternatives that closely align with actual results. Consequently, the group encountered multi-criteria decision-making (MCDM) problems, which have become increasingly significant with the rapid proliferation of information. When confronted with MCDM problems, individuals often rely on personal heuristics to weigh the pros and cons of different conditions and use accumulated group experience to make preferred decisions. However, these heuristics are frequently influenced by the group’s environmental experience, which can skew statistical data, leading to biased results rather than reflecting linear or symmetrical non-linear results. To address this, this study uses the collected group data as a basis, applies maximum likelihood estimation (MLE) to fit the data, and derives parameters that describe the group probability distribution. These parameters establish a cumulative distribution function (CDF) that represents group experience, resulting in a sigmoid function that effectively captures this experience. This sigmoid function serves as an evaluation benchmark in decision-making. Combined with a two-stage weight calculation method, a “feedforward neural network decision-making system based on group experience” was developed. Using real estate information from Taiwan as a simulation example, this decision-making system effectively and rapidly searches for real estate market information through group experience and objective assessment of the importance of each evaluation criterion, providing an appropriate decision-making basis for real estate transactions.</div></div>","PeriodicalId":48648,"journal":{"name":"Ain Shams Engineering Journal","volume":"16 9","pages":"Article 103552"},"PeriodicalIF":6.0,"publicationDate":"2025-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144297375","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}