To reveal quality change rules and establish the predicting model of konjac vacuum drying, a response surface methodology was adopted to optimize and analyze the vacuum drying process, while an artificial neural network (ANN) was applied to model the...
The present study adopted a response surface methodology (RSM) approach validated by artificial neural network (ANN) models to optimise the production of a bitter gourd-grape beverage. Aset of statistically pre-designed experiments were conducted, an...
The present study evaluates and compares predictions on the performance and the approaches of the response surface methodology (RSM) and the artificial neural network (ANN) so to model the bending strength of the polyurethane foam-cored sandwich pane...
Lead (Pb) is well known for the containment of soil surfaces. In the last few decades, phytoremediation has been the most ideal technology to extract Pb from soil, involving numerous chemical reactions and cost analysis. The aim of this study is to m...
Membrane fouling is a major hindrance to widespread wastewater treatment applications. This study optimizes operating parameters in membrane rotating biological contactors (MRBC) for maximized membrane fouling through Response Surface Methodology (RS...
Harnessing the synergistic potential of graphene oxide-doped titanium dioxide (GO-TiO2), this study pioneers an advanced photocatalytic approach by incorporating graphene oxide-doped titanium dioxide (GO-TiO2) as a catalyst to enhance the photocataly...
In this study, the response surface method (RSM), back propagation neural network (BPNN), and genetic algorithm (GA) were used for modeling and multi-objective optimization of the forming parameters of AA5052 in incremental sheet forming (ISF). The o...
As a key parameter in the adsorption process, removal rate is not available under most operating conditions due to the time and cost of experimental testing. To address this issue, evaluation of the efficiency of NH4+ removal from stormwater by coal-...
Green forage maize harvesters face challenges such as high soil humidity and soft soil in the field, mismatched working parameters, and poor reliability and adaptability. These challenges often result in header blockage, significant harvest loss, and...
Nickel ions from aqueous solutions were removed by micellar-enhanced ultrafiltration (MEUF), using the surfactant sodium dodecyl sulfate (SDS) as a chelating agent. Process variables and indicators were modeled and optimized by a response surface met...
Bioethanol production has seen an increasing trend in research recently, with a focus on increasing its economic viability. The aim of this study is to develop a low-cost fermentation medium with a minimum of redundant nutritional supplements, thereb...
Few empirical and semi-empirical approaches have considered the influence of the geology, tectonic source, causative fault type, and frequency content of earthquake motion on lateral displacement caused by liquefaction (DH). This paper aims to addres...
This study investigates the prediction of immediate settlement (Uz) in soft clay improved with Deep Soil Mixing (DSM) columns under heavy aircraft loading. Two key design parameters were considered: column spacing (2.25 m to 3.75 m) and column length...
Liquefaction is one of the most destructive phenomena caused by earthquakes, and it has been studied regarding the issues of risk assessment and hazard analysis. The strain energy approach is a common method to evaluate liquefaction triggering. In th...
Electrocoagulation (EC) employing aluminum–aluminum (Al–Al) electrodes was investigated for hospital wastewater treatment, targeting the removal of turbidity, soluble chemical oxygen demand (sCOD), and total dissolved solids (TDS). A hybr...
As the demand for sustainable construction materials grows, wood ash and nanosilica have emerged as promising components for eco-friendly mortars, whose optimization requires advanced analytical techniques capable of capturing their complex linear an...
Empirical and machine learning models are estimation tools relevant to obtaining scalable solutions to engineering problems. In this study, response surface methodology (RSM) was incorporated to correlate the experimental findings based on mathematic...
This paper deals with the development and comparison of prediction models established using response surface methodology (RSM) and artificial neural network (ANN) for a wire electrical discharge machining (WEDM) process. The WEDM experiments were des...
The integration of computational intelligence techniques into pharmaceutical wastewater treatment offers promising opportunities to improve process efficiency and minimize operational costs. This study compares the predictive capabilities of Response...
Robotic vertebral plate cutting poses significant challenges due to the complex bone structures of the lumbar spine, which consist of varying densities in cortical and cancellous regions. This study addresses these challenges by developing a predicti...
The incorporation of biodegraded substrates during the germination of horticultural crops has shown favorable responses in different crops; however, most of these studies evaluate their effect only in the first days of seedling life, and do not follo...
Prodigiosin, a red pigment with diverse biotechnological applications, is produced as a secondary metabolite by Gram-negative bacilli Serratia marcescens. In this study, we implemented an AI-guided hybrid optimization framework combining Response Sur...
Many factors (material properties, drill bit type and size, drill bit wear, drilling parameters used, and machine-tool characteristics) affect the efficiency of the drilling process, which could be quantified through the delamination factor, thrust f...
Multiple-factor analysis and optimization play a critical role in the the ability to maximizethe stimulated reservoir volume (SRV) and the success of economic shale gas production. In this paper, taking the typical continental naturally fractured sil...
This study converted pecan shell waste into magnetic Fe3O4@biocarbon for arsenic (V) removal from aqueous medium. A preliminary test was conducted on a binary system of arsenic (V) and lead. A dual-optimization approach was applied using a fuzzy deci...
The development of heterostructures incorporating photocatalysts optimized for visible-light activity represents a major breakthrough in the field of environmental remediation research, offering innovative and sustainable solutions for environmental...
In this study, coconut oils have been transesterified with ethanol using microwave technology. The product obtained (biodiesel and FAEE) was then fractional distillated under vacuum to collect bio-kerosene or bio-jet fuel, which is a renewable fuel t...
The effects of different ultrasound parameters on some physicochemical properties and secoiridoid compositions of olive extracts were investigated. For this purpose, pH, acidity, photometric color index (PCI), total phenolic content, and secoiridoid...
Ribonucleoprotein complexes are essential regulatory components in bacteria. In this review, we focus on the carbon storage regulator (Csr) network, which is well conserved in the bacterial world. This regulatory network is composed of the CsrA maste...
Weld quality plays a critical role in ensuring the structural integrity and long-term performance of critical piping systems used across petrochemical, oil and gas, marine, and healthcare sectors. Although gas tungsten arc welding, shielded metal arc...
Selective Laser Melting (SLM) of 316L stainless steel was studied with a focus on the combined influence of laser power and scan speed on tensile behavior. A full factorial design generated 27 experiments, and mechanical properties (yield stress, ult...
The incorporation of graphene into cellulose matrices has emerged as a promising strategy for enhancing the structural and functional properties of composite materials. This comprehensive review provides a critical analysis of recent advances in opti...
Chitosan was hydro-thermally extracted from grey shrimp carapaces and characterized using various techniques (degree of deacetylation (DD), viscosity, thermogravimetric analysis (TGA), scanning electron microscopy (SEM), and surface area analysis (BE...
Recent research has focused on assessing the effectiveness of response surface methodology (RSM), a non-machine learning technique, and artificial neural networks (ANN), a machine learning approach, for predicting concrete performance. This research...
In this study, the response surface methodology (RSM) and artificial neural network (ANN) were employed to study the adsorption process of 2,4-dichlorophenoxyacetic acid (2,4-D) by using modified hydrogel, i.e., activated carbon poly(dimethylaminoeth...
Waste streams with high ammonia nitrogen (NH3-N) concentrations are very commonly produced due to human intervention and often end up in waterbodies with effluent discharge. The removal of NH3-N from wastewater is therefore of utmost importance to al...
Machine learning and response surface methods for predicting the compressive strength of high-strength concrete have not been adequately compared. Therefore, this research aimed to predict the compressive strength of high-strength concrete (HSC) usin...
In the Design of Experiments, we seek to relate response variables to explanatory factors. Response Surface methodology (RSM) approximates the relation between output variables and a polynomial transform of the explanatory variables using a linear mo...
In today’s food industry, optimizing the recovery of high-value compounds is crucial for enhancing quality and yield. Multivariate methods like Response Surface Methodology (RSM) and Artificial Neural Networks (ANNs) play key roles in achieving...
This study proposes a novel Deep Reinforcement Learning (DRL) policy network structure for portfolio management called PortRSMs. PortRSMs employs stacked State-Space Models (SSMs) for the modeling of multi-scale continuous regime shifts in financial...
This paper presents an improved artificial neural network (ANN) training using response surface methodology (RSM) optimization for membrane flux prediction. The improved ANN utilizes the design of experiment (DoE) technique to determine the neural ne...
In this paper, an experimental study was conducted to determine the effect of different cutting parameters such as cutting speed, feed rate, and depth of cut on cutting force, surface roughness, and tool wear in the milling of Ti-6242S alloy using th...
The forward osmosis (FO) process is an emerging technology that has been considered as an alternative to desalination due to its low energy consumption and less severe reversible fouling. Artificial neural networks (ANNs) and response surface methodo...
In this study, circulating fluidized bed fly ash (CFBFA) non-sintered ceramsite was innovatively developed. The CFBFA was addressed by adding ternary activator (including cement, hydrated lime, and gypsum) to prepare ceramsite. In the curing process,...
Pseudomonas aeruginosa is a multi-drug-resistant opportunistic pathogen that adapts to challenging environments by deploying virulence factors, including the type III secretion system (T3SS). Emerging evidence points to a role for NADH dehydrogenase...
In robust design (RD) modeling, the response surface methodology (RSM) based on the least-squares method (LSM) is a useful statistical tool for estimating functional relationships between input factors and their associated output responses. Neural ne...
This research provides a comparative analysis of the optimization of ultra-high-performance concrete (UHPC) using artificial neural network (ANN) and response surface methodology (RSM). By using ANN and RSM, the yield of UHPC was modeled and optimize...
Time series classification (TSC) task is one of the most significant topics in data mining. Among all methods for this issue, the deep-learning-based shows superior performance for its good adaption to raw series data and automatic extraction of feat...
To determine dietary metabolizable energy (ME) and crude protein (CP) levels of Hy-Line Brown male chicks and compare response surface methodology (RSM) with artificial neural network (ANN) modeling, a total of 2160 birds were assigned to a 4 ×...
This study presents a comprehensive structural performance analysis of a honeycomb-core substrate under normal pressure, highlighting the superior predictive accuracy of Artificial Neural Networks (ANNs) over Response Surface Methodology (RSM). The a...
of 6