Search results for "PPO"
showing 10 items of 5642 documents
Assembly Assistance System with Decision Trees and Ensemble Learning
2021
This paper presents different prediction methods based on decision tree and ensemble learning to suggest possible next assembly steps. The predictor is designed to be a component of a sensor-based assembly assistance system whose goal is to provide support via adaptive instructions, considering the assembly progress and, in the future, the estimation of user emotions during training. The assembly assistance station supports inexperienced manufacturing workers, but it can be useful in assisting experienced workers, too. The proposed predictors are evaluated on the data collected in experiments involving both trainees and manufacturing workers, as well as on a mixed dataset, and are compared …
The Advantage of Digital Decision Making for Strategic Decisions – Proofed by a Supply Chain Case
2017
This paper will discuss the advantage of decision making supported by a digital system and will provide an overview of an empiric analysis researched on this topic. Decision making in organizations is a significant system implied task of managers and therefore a broad area in scientific research, not only in the disciplines management or business studies – even from technical to humanistic disciplines. Nowadays the trend of digitalization captures all areas of life especially in business, as well as the typical management task of decision making. Triggered by the digitalization trend business will move toward an autonomous decision making of machines or cyber systems. The important step tow…
Collaboration and Decision-Making in Context
2016
The goal of this chapter is to provide a historical account of the evolutions in the domain of the book and to set the stage for the concepts and solutions to be presented in the following chapters, including the introduction of the terminology adopted to be used throughout this text. Consequently, we aim at providing the answers to a series of questions, such as: (a) “How the organizations have been evolving over the last decades?”, (b) “Which have been the corresponding trends of the management and control schemes?”, (c) “How management and control functions are allocated to human and automation equipment?”, (d) “Which are the desirable properties of the information processing tools meant…
Propulsion monitoring system for digitized ship management: Preliminary results from a case study
2020
Abstract The paradigm of Industry 4.0 a fundamental driver of innovation in marine industry, where the new digital era will see the development of smart cyber-ships equipped with advanced automation systems that will progressively evolve towards fully autonomous vessels. Although the journey towards such technological frontier has started, most companies operating in the maritime sector still appear un-prepared to face the future scenario. In the maritime sector, in fact, empirical models and oversimplified approaches are still largely employed for the management of fleet operations. There is thus the necessity of developing and providing operative models for digitized ship management, whic…
A comparative assessment of energy demand and life cycle costs for additive- and subtractive-based manufacturing approaches
2020
Abstract The applicability domain of Additive Manufacturing (AM) processes, apart from technological and quality results, relies on environmental and cost performance. These aspects still need to be better understood. To this aim, comparative analyses with conventional manufacturing routes are needed. In this paper, empirical cost and energy requirement models are suggested to assess subtractive- (machining) and additive- (Electron Beam Melting) based manufacturing approaches for the production of Ti-6Al-4V components. A life-cycle perspective is adopted, and all the steps from the input material production to the post-AM processing operations and the use phase are included. The analyses ha…
Food tray sealing fault detection using hyperspectral imaging and PCANet
2020
Abstract Food trays are very common in shops and supermarkets. Fresh food packaged in trays must be correctly sealed to protect the internal atmosphere and avoid contamination or deterioration. Due to the speed of production, it is not possible to have human quality inspection. Thus, automatic fault detection is a must to reach high production volume. This work describes a deep neural network based on Principal Component Analysis Network (PCANet) for food tray sealing fault detection. The input data come from hyperspectral cameras, showing more characteristics than regular industrial cameras or the human eye as they capture the spectral properties for each pixel. The proposed classification…
Adjusted bat algorithm for tuning of support vector machine parameters
2016
Support vector machines are powerful and often used technique of supervised learning applied to classification. Quality of the constructed classifier can be improved by appropriate selection of the learning parameters. These parameters are often tuned using grid search with relatively large step. This optimization process can be done computationally more efficiently and more precisely using stochastic search metaheuristics. In this paper we propose adjusted bat algorithm for support vector machines parameter optimization and show that compared to the grid search it leads to a better classifier. We tested our approach on standard set of benchmark data sets from UCI machine learning repositor…
MFNet: Multi-feature convolutional neural network for high-density crowd counting
2020
The crowd counting task involves the issue of security, so now more and more people are concerned about it. At present, the most difficult problem of population counting consists in: how to make the model distinguish human head features more finely in the densely populated area, such as head overlap and how to find a small-scale local head feature in an image with a wide range of population density. Facing these challenges, we propose a network for multiple feature convolutional neural network, which is called MFNet. It aims to get high-quality density maps in the high-density crowd scene, and at the same time to perform the task of the count and estimation of the crowd. In terms of crowd c…
An Artificial Bee Colony Approach for Classification of Remote Sensing Imagery
2018
This paper presents a novel Artificial Bee Colony (ABC) approach for supervised classification of remote sensing images. One proposes to apply an ABC algorithm to optimize the coefficients of the set of polynomial discriminant functions. We have experimented the proposed ABC-based classifier algorithm for a Landsat 7 ETM+ image database, evaluating the influence of the ABC model parameters on the classifier performances. Such ABC model parameters are: numbers of employed/onlooker/scout bees, number of epochs, and polynomial degree. One has compared the best ABC classifier Overall Accuracy (OA) with the performances obtained using a set of benchmark classifiers (NN, NP, RBF, and SVM). The re…
PolyACO+: a multi-level polygon-based ant colony optimisation classifier
2017
Ant Colony Optimisation for classification has mostly been limited to rule based approaches where artificial ants walk on datasets in order to extract rules from the trends in the data, and hybrid approaches which attempt to boost the performance of existing classifiers through guided feature reductions or parameter optimisations. A recent notable example that is distinct from the mainstream approaches is PolyACO, which is a proof of concept polygon-based classifier that resorts to ant colony optimisation as a technique to create multi-edged polygons as class separators. Despite possessing some promise, PolyACO has some significant limitations, most notably, the fact of supporting classific…