The vision system provides an important way for construction robots to obtain the type and spatial location information of the object. The characteristics of the construction environment, construction object, and robot structure are jointly examined...
The profession debates how to encode a categorical variable for input to machine learning algorithms, such as neural networks. A conventional approach is to convert a categorical variable into a collection of binary variables, which causes a burdenso...
Traditional drug development is a slow and costly process that leads to the production of new drugs. Virtual screening (VS) is a computational procedure that measures the similarity of molecules as one of its primary tasks. Many techniques for captur...
Predicting crop yields is one of agriculture’s most challenging issues. It is crucial in making national, provincial, and regional choices and estimates the government to meet the food demands of its citizens. Crop production is anticipated bas...
Recently, many convolutional neural network (CNN)-based methods have been proposed to tackle the classification task of hyperspectral images (HSI). In fact, CNN has become the de-facto standard for HSI classification. It seems that the traditional ne...
It is necessary to predict dam inflow in advance for flood prevention and stable dam operations. Although predictive models using deep learning are increasingly studied, these existing studies have merely applied the models or adapted the model struc...
Centrifugal pumps (CPs) are widely utilized in many different industries, and their operations are maintained by their reliable performance. CPs’ most common faults can be categorized as mechanical or flow-related faults: the first ones are oft...
Due to emerging internet technologies that mostly depend on the decentralization concept, such as cryptocurrencies, cyber attackers also use the decentralization concept to develop P2P botnets. P2P botnets are considered one of the most serious and c...
This paper introduces a parallel meta-heuristic algorithm called Cuckoo Flower Search (CFS). This algorithm combines the Flower Pollination Algorithm (FPA) and Cuckoo Search (CS) to train Multi-Layer Perceptron (MLP) models. The algorithm is evaluate...
To achieve an acceptable level of security on the web, the Completely Automatic Public Turing test to tell Computer and Human Apart (CAPTCHA) was introduced as a tool to prevent bots from doing destructive actions such as downloading or signing up. S...
In recent wind power forecasting studies, deep neural networks have shown powerful performance in estimating future power from wind power data. In this paper, a pseudo-twin neural network model of full multi-layer perceptron is proposed for power for...
With the proliferation of mobile devices, the popularity of Android applications (apps) has increased exponentially. Efficient power consumption in a device is essential from the perspective of the user because users want their devices to work all da...
To better understand and evaluate the GNSS positioning performance, it is convenient to adopt corresponding measures to reduce the impact of errors on positioning. A GNSS positioning error estimation scheme based on an improved multi-layer perceptron...
We aim to detect outliers in the daily stock price indices from the Saudi Arabia stock exchange (Tadawul) with 2026 observations from October 2011 to December 2019 provided by the Saudi Authority for Statistics and the Saudi Central Bank. We apply th...
As autonomous driving technology advances, the imperative of ensuring pedestrian traffic safety becomes increasingly prominent within the design framework of autonomous driving systems. Pedestrian trajectory prediction stands out as a pivotal technol...
Optimizing concrete production requires balancing ingredient ratios and using local resources to produce an economical material with the desired consistency, strength, and durability. Compressive strength is crucial for structural design, yet predict...
The implementation of corrosion detection in submarine pipelines is difficult, and a combined PCA-MLP prediction model is proposed to improve the accuracy of corrosion prediction in submarine pipelines. Firstly, the corrosion rate of a submarine mult...
Remote sensing of land surface temperature (LST) is a fundamental variable in analyzing temperature variability in urban areas. Geostationary sensors provide sufficient observations throughout the day for a diurnal analysis of temperature, however, l...
Metaheuristic optimization algorithms play a crucial role in optimization problems. However, the traditional identification methods have the following problems: (1) difficulties in nonlinear data processing; (2) high error rates caused by local stagn...
A Multi-Layer Perceptron (MLP), as the basic structure of neural networks, is an important component of various deep learning models such as CNNs, RNNs, and Transformers. Nevertheless, MLP training faces significant challenges, with a large number of...
The purpose of this study is to investigate and compare the popularity of common grocery apps in Hungary as well as Iran. The data were gathered from Iranian and Hungarian users who had at least one online purchase experience using a grocery app. A G...
Waterway networking environments present unique challenges due to their dynamic nature, including vessel movement, water flow, and varying water quality. These challenges render traditional static surveillance systems inadequate for effective monitor...
Background: Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is an imaging technique which helps in visualizing and quantifying perfusion—one of the most important indicators of an organ’s state. This paper focuses on perfus...
With the increasing demand for location-based services, Wi-Fi-based indoor positioning technology has attracted much attention in recent years because of its ubiquitous deployment and low cost. Considering that Wi-Fi signals fluctuate greatly with ti...
Background/Objectives: Diabetic retinopathy (DR) remains one of the primary causes of preventable vision impairment worldwide, particularly among individuals with long-standing diabetes. The progressive damage of retinal microvasculature can lead to...
In this paper a genetic algorithm (GA) approach to design of multi-layer perceptron (MLP) for combined cycle power plant power output estimation is presented. Dataset used in this research is a part of publicly available UCI Machine Learning Reposito...
In the present scenario, Alzheimer’s Disease (AD) is one of the incurable neuro-degenerative disorders, which accounts for nearly 60% to 70% of dementia cases. Currently, several machine-learning approaches and neuroimaging modalities are utili...
The smart regenerative braking system (SRS) is an autonomous version of one-pedal driving in electric vehicles. To implement SRS, a deceleration planning algorithm is necessary to generate the deceleration used in automatic regenerative control. To r...
Resonant controllers are widely used in power electronics to track sinusoidal references. According to the internal model principle (IMP), these controllers should embed the poles of the Laplace or Z transform of the reference for the closed-loop sys...
Land-use and land-cover change (LULCC) is a critical environmental issue that has significant effects on biodiversity, ecosystem services, and climate change. This study examines the land-use and land-cover (LULC) spatiotemporal dynamics across a thr...
This study analyzed the changes of land use and land cover (LULC) in New Jersey in the United States from 2007 to 2012. The goal was to identify the driving factors of these changes and to project the five-year trend to 2100. LULC data was obtained f...
Runoff in urban streams is the most important factor influencing urban inundation. It also affects inundation in other areas as various urban streams and rivers are connected. Current runoff predictions obtained using a multi-layer perceptron (MLP) e...
The aim of the research work is to investigate the operability of the entire 23 pulmonary function parameters, which are stipulated by the American Thoracic Society (ATS) and the European Respiratory Society (ERS), to design a medical decision suppor...
In this study, urban growth of the Atakum District in Samsun, Turkey, was simulated by Cellular Automata-Markov Chain (CA-MC) and Multi-layer Perceptron-Markov Chain (MLP-MC) hybrid models in a geographical information system (GIS) environment. Histo...
The spatial and spectral information brought by the Very High Resolution (VHR) and multispectral satellite images present an advantage for Satellite-Derived Bathymetry (SDB), especially in shallow-water environments with dense wave patterns. This wor...
Shipborne gravity can be used to refine altimeter-derived gravity whose accuracy is low in shallow waters and areas with complex submarine topography. As altimeter-derived gravity only within a small radius around the shipborne data can be corrected...
An efficient Battery Management System (BMS) specifically for Electric Vehicles is crucial for improving battery run time performance. A primary function of an effective BMS is accurately determining the State of Charge (SOC) and State of Health (SOH...
Urban expansion is considered as one of the most important problems in several developing countries. Bangkok Metropolitan Region (BMR) is the urbanized and agglomerated area of Bangkok Metropolis (BM) and its vicinity, which confronts the expansion p...
This study investigates the application of a coupled multi-layer perceptrons (MLP) model with Archimedes optimizer (AO) to predict characteristics of dissimilar lap joints made of polymethyl methacrylate (PMMA) and polycarbonate (PC). The joints were...
The rapid growth of the aviation industry and increasing air traffic demand more careful attention to environmental concerns. Among these, aircraft noise is considered one of the main sources of environmental noise, especially after land-based transp...
The recent development of algorithms through artificial intelligence and the ability to measure the human body through soft textile sensors has enabled the provision of meaningful information to the wearer. In this study, a sensor sleeve using a text...
As conventional data storage systems are faced with critical problems such as the superparamagnetic limit, bit-patterned media recording (BPMR) has received significant attention as a promising next-generation magnetic data storage system. However, t...
This study investigates the use of surface electromyography (sEMG) sensors in measuring muscle activity and mapping it onto wearable textile stretch sensors using a basic deep learning model, the Multi-Layer Perceptron (MLP). Wearable sensors are gai...
At present, the amount of network equipment, servers, and network traffic is increasing exponentially, and the way in which operators allocate and efficiently utilize network resources has attracted considerable attention from traffic forecasting res...
In this study, we propose a method of classification for tympanic membrane diseases and regression of pediatric hearing, using a deep learning model of artificial neural networks. Based on the B7 Backbone model of EfficientNet, a state-of-the-art con...
Service recommendation is key to improving users’ online experience. The development of the Internet has accelerated the creation of many services, and whether users can obtain good experiences among the massive number of services mainly depend...
Supply chain management is essential for businesses to handle uncertainties, maintain efficiency, and stay competitive. Financial risks can arise from various internal and external sources, impacting different supply chain stages. Companies that effe...
Amid global efforts toward carbon neutrality, carbon emission accounting in the construction sector has become essential for sustainable design. Public buildings, with complex energy systems and high operational loads, are major carbon emitters. Howe...
Atmospheric pollutants’ real-time changes and the internal interactions among various data make it challenging to efficiently predict concentration variations. In order to extract more information from the time series of pollutants and improve...
During energy transition, where sustainability and environmental protection are increasingly prioritized, ensuring safety in coal exploitation remains a critical issue, especially in the context of worker safety. This research focuses on predicting m...
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