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Wyniki wyszukiwania dla: classification, optimization
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Impact of optimization of ALS point cloud on classification
PublikacjaAirborne laser scanning (ALS) is one of the LIDAR technologies (Light Detection and Ranging). It provides information about the terrain in form of a point cloud. During measurement is acquired: spatial data (object’s coordinates X, Y, Z) and collateral data such as intensity of reflected signal. The obtained point cloud is typically applied for generating a digital terrain model (DTM) and a digital surface model (DSM). For DTM...
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CLASSIFICATION OF RESTRAINTS IN THE OPTIMIZATION PROBLEM OF A COLD-FORMED PROFILE
PublikacjaThis work describes the restraints in the optimization problem. This is an important and complicated issue because it requires taking into account a vast range of information related to the design and production. In order to describe the relations of a specific optimization problem, it is essential to adopt appropriate criteria and to collect information on all kinds of restraints, i.e. boundary conditions. The following paper...
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Multiplicative Long Short-Term Memory with Improved Mayfly Optimization for LULC Classification
PublikacjaLand Use and Land Cover (LULC) monitoring is crucial for global transformation, sustainable land control, urban planning, urban growth prediction, and the establishment of climate regulations for long-term development. Remote sensing images have become increasingly important in many environmental planning and land use surveys in recent times. LULC is evaluated in this research using the Sat 4, Sat 6, and Eurosat datasets. Various...
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Classification of Covid-19 using Differential Evolution Chaotic Whale Optimization based Convolutional Neural Network
PublikacjaCOVID-19, also known as the Coronavirus disease-2019, is an transferrable disease that spreads rapidly, affecting countless individuals and leading to fatalities in this worldwide pandemic. The precise and swift detection of COVID-19 plays a crucial role in managing the pandemic's dissemination. Additionally, it is necessary to recognize COVID-19 quickly and accurately by investigating chest x-ray images. This paper proposed a...
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Swarm Algorithms in Modern Engineering Optimization Problems
PublikacjaComplexity of today engineering problems is constantly increasing. Scientists no longer are facing issues, for which simple, mathematical programming methods are sufficient. Issues like autonomic vehicle navigation or classification are considered to be challenging, and although there exist valid means to solve them, in some cases there still is some place for improvement. With emergence of a new type of optimization techniques...
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Musical Instrument Separation Applied to Music Genre Classification . Separacja instrumentów muzycznych w zastosowaniu do rozpoznawania gatunków muzycznych
PublikacjaThis paper outlines first issues related to music genre classification and a short description of algorithms used for musical instrument separation. Also, the paper presents proposed optimization of the feature vectors used for music genre recognition. Then, the ability of decision algorithms to properly recognize music genres is discussed based on two databases. In addition, results are cited for another database with regard to...
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Multimodal Particle Swarm Optimization with Phase Analysis to Solve Complex Equations of Electromagnetic Analysis
PublikacjaIn this paper, a new meta-heuristic method of finding roots and poles of a complex function of a complex variable is presented. The algorithm combines an efficient space exploration provided by the particle swarm optimization (PSO) and the classification of root and pole occurrences based on the phase analysis of the complex function. The method initially generates two uniformly distributed populations of particles on the complex...
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Tool Wear Monitoring Using Improved Dragonfly Optimization Algorithm and Deep Belief Network
PublikacjaIn recent decades, tool wear monitoring has played a crucial role in the improvement of industrial production quality and efficiency. In the machining process, it is important to predict both tool cost and life, and to reduce the equipment downtime. The conventional methods need enormous quantities of human resources and expert skills to achieve precise tool wear information. To automatically identify the tool wear types, deep...
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An automated learning model for twitter sentiment analysis using Ranger AdaBelief optimizer based Bidirectional Long Short Term Memory
PublikacjaSentiment analysis is an automated approach which is utilized in process of analysing textual data to describe public opinion. The sentiment analysis has major role in creating impact in the day-to-day life of individuals. However, a precise interpretation of text still relies as a major concern in classifying sentiment. So, this research introduced Bidirectional Long Short Term Memory with Ranger AdaBelief Optimizer (Bi-LSTM RAO)...
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Method of Decision-Making Logic Discovery in the Business Process Textual Data
PublikacjaGrowing amount of complexity and enterprise data creates a need for novel business process (BP) analysis methods to assess the process optimization opportunities. This paper proposes a method of BP analysis while extracting the knowledge about Decision-Making Logic (DML) in a form of taxonomy. In this taxonomy, researchers consider the routine, semi-cognitive and cognitive DML levels as functions of BP conceptual aspects of Resources,...
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Energy-Aware High-Performance Computing: Survey of State-of-the-Art Tools, Techniques, and Environments
PublikacjaThe paper presents state of the art of energy-aware high-performance computing (HPC), in particular identification and classification of approaches by system and device types, optimization metrics, and energy/power control methods. System types include single device, clusters, grids, and clouds while considered device types include CPUs, GPUs, multiprocessor, and hybrid systems. Optimization goals include various combinations of...
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Application of Multivariate Adaptive Regression Splines (MARSplines) for Predicting Hansen Solubility Parameters Based on 1D and 2D Molecular Descriptors Computed from SMILES String
PublikacjaA new method of Hansen solubility parameters (HSPs) prediction was developed by combining the multivariate adaptive regression splines (MARSplines) methodology with a simple multivariable regression involving 1D and 2D PaDEL molecular descriptors. In order to adopt the MARSplines approach to QSPR/QSAR problems, several optimization procedures were proposed and tested. The effectiveness of the obtained models was checked via standard...
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A comparative study of English viseme recognition methods and algorithm
PublikacjaAn elementary visual unit – the viseme is concerned in the paper in the context of preparing the feature vector as a main visual input component of Audio-Visual Speech Recognition systems. The aim of the presented research is a review of various approaches to the problem, the implementation of algorithms proposed in the literature and a comparative research on their effectiveness. In the course of the study an optimal feature vector...
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A comparative study of English viseme recognition methods and algorithms
PublikacjaAn elementary visual unit – the viseme is concerned in the paper in the context of preparing the feature vector as a main visual input component of Audio-Visual Speech Recognition systems. The aim of the presented research is a review of various approaches to the problem, the implementation of algorithms proposed in the literature and a comparative research on their effectiveness. In the course of the study an optimal feature vector construction...
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Aeration Process in Bioreactors as the Main Energy Consumer in a Wastewater Treatment Plant. Review of Solutions and Methods of Process Optimization
PublikacjaDue to the key role of the biological decomposition process of organic compounds in wastewater treatment, a very important thing is appropriate aeration of activated sludge, because microorganisms have to be supplied with an appropriate amount of oxygen. Aeration is one of the most energy-consuming processes in the conventional activated sludge systems of wastewater treatment technology (may consume from 50% to 90% of electricity...
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DETERMINATION OF OBJECTIVES FOR URBAN FREIGHT POLICY
PublikacjaBackground: Decisions regarding strategic planning of urban freight transport very often are based on superficial assumptions inadequately reflecting the actual character of encountered challenges. The trend may be observed to adapt isolated solutions without supporting measures and verification of expected outcomes. Selected urban freight solutions have a significant potential to alleviate transport related problems, but they...
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Weighted Clustering for Bees Detection on Video Images
PublikacjaThis work describes a bee detection system to monitor bee colony conditions. The detection process on video images has been divided into 3 stages: determining the regions of interest (ROI) for a given frame, scanning the frame in ROI areas using the DNN-CNN classifier, in order to obtain a confidence of bee occurrence in each window in any position and any scale, and form one detection window from a cloud of windows provided by...
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Voice command recognition using hybrid genetic algorithm
PublikacjaAbstract: Speech recognition is a process of converting the acoustic signal into a set of words, whereas voice command recognition consists in the correct identification of voice commands, usually single words. Voice command recognition systems are widely used in the military, control systems, electronic devices, such as cellular phones, or by people with disabilities (e.g., for controlling a wheelchair or operating a computer...
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Towards Understanding the Health Aspects of the Processing of Lignocellulosic Fillers
PublikacjaHealth and safety issues should be addressed during the development and investigation of the industrial processes. In order to develop a sustainable process and fully evaluate its benefits and drawbacks for its optimization, it is crucial to determine its impact on the surrounding environment. This study aimed to assess the emission of volatile organic compounds during the modification of lignocellulosic fillers with passive dosimetry....
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Neural network training with limited precision and asymmetric exponent
PublikacjaAlong with an extremely increasing number of mobile devices, sensors and other smart utilities, an unprecedented growth of data can be observed in today’s world. In order to address multiple challenges facing the big data domain, machine learning techniques are often leveraged for data analysis, filtering and classification. Wide usage of artificial intelligence with large amounts of data creates growing demand not only for storage...