Wyniki wyszukiwania - BazTech

1

Sztuczne inteligencje i biologiczne mózgi

Durka Piotr

Postępy Fizyki

|

2025

|

T. 76, z. 1

3--12

PL

Sztuczna inteligencja (ang. artificial intelligence, AI) to najgorętszy temat ostatnich lat, nie tylko w technologii. Jest wszędzie - od szczoteczek do zębów po artykuły naukowe. Pochłania setki miliardów dolarów, trzęsie giełdami, podważa wiarę w prawdziwość cyfrowych treści, halucynuje i karmi apokaliptyczne przepowiednie. Czym naprawdę jest AI? Czy zamiast Artificial Intelligence powinniśmy mówić o Alien Intelligence, jak sugeruje Yuval Noah Harari, czy raczej oczekiwać połączenia inteligencji białkowej z krzemową przez interfejsy mózg-komputer, razem z Raymondem Kurzweilem? Dlaczego wykorzystująca zdobycze nauki cywilizacja skręca nagle w stronę czarnych skrzynek i tajemniczych wyroczni? Spróbujemy określić, czym jest AI, i wyjaśnimy czym nie jest, demaskując po drodze kilka miejskich legend o podsłuchiwaniu myśli i przenoszeniu świadomości do cyberprzestrzeni. Omówimy też realne zagrożenia wynikające z faktu, że od od lat oddajemy algorytmom rząd dusz, ale nie zauważamy tego wsłuchani w opowieści o nadchodzącej „apokalipsie AI”.

EN

Artificial Intelligence (AI) is the hottest topic of recent years, and not only in technology. It is everywhere - from toothbrushes to scientific articles. It consumes hundreds of billions of dollars, shakes stock markets, undermines the credibility of digital content, hallucinates and feeds apocalyptic prophecies. What is AI really? Should we understand Artificial Intelligence as Alien Intelligence, as Yuval Noah Harari suggests, or rather expect biological intelligence to merge with silicon intelligence via brain-computer interfaces, together with Raymond Kurzweil? Why does our science-based civilization suddenly turn towards black boxes and mysterious oracles? We will try to define what AI is and explain what it is not, along the way debunking a few urban legends about eavesdropping on thoughts and transferring consciousness to cyberspace. We will also discuss the real threats resulting from the fact that for years we have been giving the reign of our souls to algorithms, but we do not notice it, listening to stories about the coming “AI apocalypse”.

2

High availability model of a web service from a system administrator’s perspective

Wirski Robert Tomasz

Zeszyty Naukowe Politechniki Morskiej w Szczecinie

|

2024

|

nr 77 (149)

99--106

EN

Based on cloud providers’ reports on service outages, it has become clear that how a web service is deployed is of great importance. Clearly, using one service supplier is insufficient because it introduces single points of failure. In this paper, a novel high-availability multi-cloud model intended for a web service is proposed, which is free from such shortcomings yet preserves convenient assets of computing clouds. The methodology used to improve web service availability should involve several cloud suppliers and devise management techniques that control access to them. This is achieved by means of the server availability tracking algorithm, which controls client apps’ access to the service. Moreover, typical benefits and problems involved in choosing IT infrastructure for a web service are elaborated. State-of-the-art cloud computing models, such as IaaS, PaaS, SaaS, BPaaS, and INaaS, are outlined. Operating systems statistics used for web services are included. Open-source monitoring software solutions are gathered, which help administrators to monitor and govern web servers.

3

Przegląd algorytmów optymalizacji topologii za pomocą sieci neuronowych o otwartym kodzie

Kowalski Damian

Przegląd Budowlany

|

2024

|

R. 95, nr 7

118--123

PL

Artykuł prezentuje metody optymalizacji topologii z udziałem sztucznych sieci neuronowych wraz z implementacjami o otwartym kodzie. Algorytmy te skupiają się głównie na optymalizacji konstrukcji, jednak podjęto także próby optymalizacji przewodnictwa cieplnego oraz interakcji płyn-konstrukcja. W pracy przedstawiono porównanie istotnych cech algorytmów oraz podsumowano wyniki przeprowadzonych eksperymentów z ich użyciem. Ponadto nakreślono perspektywy i ograniczenia przy stosowaniu sztucznych sieci neuronowych do zagadnienia optymalizacji.

EN

The article presents methods of topology optimization using artificial neural networks with their open-source implementations. The algorithms are focused mainly on structural optimization, though some attempts of heat transfer and fluidstructure interaction optimizing were made. The paper presents a comparison of essential features of the algorithms and sums up conducted experiments results. Furthermore, perspectives and limitations of using artificial neural networks for optimization task were outlined.

4

Contribution to a New Algorithm to Perform an Automatic Self-Calibration of Current Sensors

Beladjine Djamel Eddine, Boudana Djamel, Moualdia Abdelhafidh, Wira Patice

Power Electronics and Drives

|

2024

|

Vol. 9 (44)

446--462

EN

Sensors calibration plays a crucial role in controlling systems and achieving fault-tolerant control by ensuring accuracy, performance, safety, energy efficiency, and compliance with standards. It is an essential to maintain the reliability and effectiveness of modern control systems across various applications. In this paper, we represent a new algorithm that processes a set of raw data collected by a sensor to find the mapping function that relates the raw data to the real value of the measured signal by the sensor. Working on sensors with an unknown mapping function, unknown parameters, or with external disturbances, that affects their behaviour, represents a problem; moreover, it takes a lot of time and effort to calibrate the sensor before each use. Several techniques were used to overcome these aspects mostly by recording the output of the sensor for different input values that change manually, to calibrate the sensor. However, the represented technique in this paper can easily provide us with the input/output model of a specific sensor by doing only one experiment; it also improves the accuracy of the measurements as it is a self-calibrating technique that reduces the nonlinearity and noise problems to deliver a better estimation of the measured signal, which is validated in this paper experimentally using a low-cost current sensor by comparing the obtained results from this algorithm with the results using the extracted input/output model illustrated in the datasheet. Furthermore, if the sensor is pretty poor, and if the application requires more precision, the provided estimation by the mapping function can be mixed with other sensor/s readings using sensor fusion algorithms to find a more precise value of the input. The represented algorithm can also perform self-calibration while evaluating the functionality of the application and the variations of the temperature and other external disturbances that affect the sensor.

5

An Algorithm for Adjustment of Geometric Levelling Networks

Cvetkov Vasil

Inżynieria Mineralna

|

2024

|

Vol. 1, no. 1

187--194

EN

The natural way to reduce the duration of measurement of a levelling network is to cut down on the number of levelling lines without damaging the quality of the final results. The main objective of the study is to demonstrate that this is possible without any lack of accuracy, if some mathematical facts regarding the average of both measurements of the line elevations are taken into account. Based on 60 paired random samples of size 1000, derived from different continuous distributions, e.g., N (0, 1), U (-1.732, 1.732) and Gamma (1, 1), each of them with theoretical standard deviation σ=1, it was found that the averages of each pair form new distribution with standard deviation σ≈0.707. However, the samples, which were formed by selecting the nearest to the known theoretical expectation from both measurements and their average have distributions, which standard deviations tend to σ≈0.53, σ≈0.46 and σ≈0.43 for the U (-1.732, 1.732), N (0, 1) and Gamma (1, 1) distributions, respectively. Therefore, if we choose the more appropriate value from the “first”, the “second” measurement and their average, we will increase the accuracy of the network almost √2 times in comparison to the accuracy, yielded by the only use of the averages. If our network contains n lines, the process of finding of these elevation values, which leads to the best fit of the network, is based on 3n single adjustments of the network. In addition, we can minimize the impact of the shape of the network on the final standard errors of the adjusted heights or geopotential numbers of the nodal benchmarks in the network, if we apply some iterative procedures, e.g., Inverse Distance Weighting (IDW), Inverse Absolute Height Weighting (IAHW), etc. In order to check the above explained algorithm, the Second Levelling of Finland network was adjusted in three variants. In the first variant, the whole network was adjusted as a free one. The classical weights w=L-1 were used. In the second variant, the network was separated into two parts. Applying 312 and 314 independent adjustments, the selection of the best fitted values of line elevations was done and the network was adjusted by using them. The IDW and IAHW with power parameter p=5 were finally applied. In the third variant, the network was separated in four parts. Applying 313, 312, 316 and 312 independent adjustments, the new selection of the line elevations was done and the network was adjusted by them. The IDW (p=6.5) and IAHW (p=6) were executed. Comparison of the standard errors of the adjusted geopotential numbers in the separate variants revealed that there was no statistically significant difference between the results, yielded in the second and the third variant. However, these variants produced 3-5 times increase of the accuracy in comparison to the classical first variant. The best results were obtained in the second variant with IAHW, where the mean value of the standard errors of the adjusted geopotential numbers is below 1.4 mgpu.

6

Formation of Models for Registering Systemic Processes in The Digital Educational Environment of the University Based on Log File Analysis

Lakhno Valerii, Akhmetov Bakhytzhan, Makulov Kaiyrbek, Tynymbayev Bauyrzhan, Tsiutsiura Svitlana, Tsiutsiura Mikola, Chubaievskyi Vitalii

International Journal of Electronics and Telecommunications

|

2024

|

Vol. 70, No. 2

389--396

EN

It has been demonstrated that technologies and methods of intelligent data analysis (IDA) in the educational domain, particularly based on the analysis of digital traces (DT) of students, offer substantial opportunities for analyzing student activities. Notably, the DT of students are generated both during remote learning sessions and during blended learning modes. By applying IDA methods to DT, one can obtain information that is beneficial for both the educator in a specific discipline and for the educational institution's management. Such information might pertain to various aspects of the functioning of the digital educational environment (DEE) of the institution, such as: the student's learning style; individual preferences; the amount of time dedicated to a specific task, among others. An algorithm has been proposed for constructing a process model in the DEE based on log analysis within the DEE. This algorithm facilitates the description of a specific process in the DEE as a hierarchy of foundational process elements. Additionally, a model based on cluster analysis methods has been proposed, which may prove beneficial for analyzing the registration logs of systemic processes within the university's DEE. Such an analysis can potentially aid in detecting anomalous behavior of students and other individuals within the university's DEE. The algorithms proposed in this study enable research during log file analysis aimed at identifying breaches of information security within the university's DEE.

7

Current approaches in traffic lane detection: a minireview

Aron Csato, Florin Mariasiu

Archiwum Motoryzacji

|

2024

|

Vol. 104, nr 2

19--47

EN

The continuous development and importance of the field of road transport these days make it necessary to design, develop and implement technological solutions that reduce (eliminate as much as possible) the risk of road accidents. Such a technological solution is also represented by advanced driver assistance systems (ADAS), systems that assist drivers in various ways, such as collision avoidance, automatic parking, adaptive cruise control, attention and lane departure warnings. Over the next ten years, there will likely be a rise in the need for ADAS system deployment in automobile construction, driven by consumer and regulatory interest in safety applications that protect drivers and lower accident rates. At the moment, autonomous emergency braking and forward collision warning systems are mandated for all cars in the US and the EU. Additionally, advanced driver assistance systems (ADAS) may soon distinguish automobile brands and have a significant impact on consumer preference. The present work aims to provide a general picture related to the current research and development of ADAS systems that refer to the detection of the traffic lane and lane markings. The approaches are presented regarding: the current development directions of ADAS systems, current traffic lane detection techniques, traffic lane detection methods and the use of artificial intelligence techniques in this field. The general conclusion is that further research is needed in the field, research to increase the performance of traffic lane detective systems by using advanced algorithms and easy-to-implement methods that do not require large hardware resources.

8

Simulation of torque variations in a diesel engine for light helicopters using PI control algorithms

Magryta Paweł, Barański Grzegorz

Applied Computer Science

|

2024

|

Vol. 20, no. 3

192--201

EN

This article presents the results of simulation research of a diesel engine for a light helicopter. The simulations were performed using the 1D software AVL Boost RT. The engine model includes elements such as cylinders, turbine, compressor, inlet and outlet valves, ambient environment definition, and fuel injection control strategy. The simulations aimed to evaluate the engine's response to step changes in the main rotor load, both increasing and decreasing power demands. Parameters analyzed included power deviation, torque, engine rotational speed, and stabilization time of the main rotor rotational speed. All tests were conducted using a single set of PI controller settings. The results demonstrate that these parameters are dependent on the magnitude of the step change in the main rotor load demand. The study compares the maximum engine rotational speed deviation from the nominal value for both increasing and decreasing main rotor load demands. The findings indicate that using PI regulator to control rotational speed in the diesel engine in a light helicopter significantly depends on the change in the load torque on the rotor.

9

K-Nearest Neighbours oraz K-Means: Zrozumienie zasad działania oraz zalet i wad

Koziara Natalia

Analit

|

2024

|

Nr 14

120--125

PL

Uczenie maszynowe jest metodą analizy danych, polegającą na automatyzacji modeli analitycznych, dzięki któremu możliwe jest uzyskanie dokładniejszych wyników. Wyróżnia się cztery rodzaje algorytmów - nadzorowane, półnadzorowane, nienadzorowane oraz wzmocnione, do których zalicza się między innymi algorytm k-najbliższych sąsiadów (K-Nearest Neighbors - KNN) oraz algorytm k-średnich (K-Means). Pierwszy z nich jest nieparametryczny, nadzorowanym klasyfikatorem uczenia się, natomiast drugi zaliczany jest do uczenia maszynowego bez nadzoru. Algorytm k-najbliższych sąsiadów używany jest w przypadku klasyfikacji oraz regresji, podczas gdy algorytm k-średnich stosowany jest w zadaniach grupowych. Oba algorytmy, dzięki wielu zaletom znajdują szerokie zastosowanie w różnorodnych dziedzinach.

EN

Machine learning is a method of data analysis that involves automating analytical models to produce more accurate results. There are four types of algorithms - supervised, semi-supervised, unsupervised and enhanced, which include the K-Nearest Neighbors (KNN) algorithm and the k-means (K-Means) algorithm. The former is a non-parametric supervised learning classifier, while the latter is classified as unsupervised machine learning. The k-nearest neighbor algorithm is used for classification and regression, while the k-means algorithm is used for clustering tasks. Both algorithms, thanks to their many advantages, are widely used in a variety of fields.

10

Implementation of Unmanned Aerial Vehicles in the Automated Assessment of Geodetic Database Validity

Maciąg Klaudia, Maciąg Michał, Leń Przemysław

Advances in Science and Technology. Research Journal

|

2024

|

Vol. 18, no. 7

379--395

EN

Nowadays, the progress of technology covers, among other things, the development of modern techniques and high technologies used in land surveys. Unmanned aerial vehicles (UAVs), as a good alternative to conventional land survey techniques, have currently played an increasing role. The advantages of using unmanned aerial vehicles in photogrammetric measurements include a relatively short mission time for large-area surveys. In addition, photogrammetric products have a wider range of applications compared with conventional geodetic surveys. Many scientific publications delve into the quality of photogrammetric products, but the accuracy of UAVs in the context of geodetic standards has not been investigated in full. In this paper, we attempt to fill the observed research gap. Our research has analysed the position of objects recorded in geodetic databases referring to their counterparts based on an accurate orthophotomap from a photogrammetry campaign employing an unmanned aerial vehicle. The outcomes were referenced with land survey accuracy standards set out by relevant legislation. To ensure a smooth assessment of the result's accuracy we designed a computing algorithm with a module for selecting comparable points and verifying the results. The tool can be implemented in surveys carried out in any area thanks to open-source GIS software. Our analysis showed that a detailed orthophotomap delivered using UAVs can be a valuable data source on objects recorded in geodetic databases covering selected cadastral and topographic objects and land development components. A general verification of the accuracy and validity of a geodetic numerical map and preliminary detection of areas for potential updates can be a particularly useful application of photogrammetry.

11

Fast Segmentation of Convex Cyst-like Structures in Gelatin Soft Tissue Phantoms under Ultrasound Imaging with Artifacts and Limited Training Samples

Drozd Dalia, Ciszkiewicz Adam

Advances in Science and Technology. Research Journal

|

2024

|

Vol. 18, no. 4

89--96

EN

Ultrasound imaging is common for surgical training and development of medical robotics systems. Recent advancements in surgical training often utilize soft-tissue phantoms based on gelatin, with additional objects inserted to represent different, typically fluid-based pathologies. Segmenting these objects from the images is an important step in the development of training and robotic systems. The current study proposes a simple and fast algorithm for segmenting convex cyst-like structures from phantoms under very low training sample scenarios. The algorithm is based on a custom two-step thresholding procedure with additional post-processing with two trainable parameters. Two large phantoms with convex cysts are created and used to train the algorithm and evaluate its performance. The train/test procedure are repeated 60 times with different dataset splits and prove the viability of the solution with only 4 training images. The DICE coefficients were on average at 0.92, while in the best cases exceeded 0.95, all with fast performance in single-thread operation. The algorithm might be useful for development of surgical training systems and medical robotic systems in general.

12

Examination of a magnetorheological damper control system with vibration energy harvesting

Jastrzębski Łukasz, Sapiński Bogdan

Acta Mechanica et Automatica

|

2024

|

Vol. 18, no. 1

158--168

EN

The study deals with the experimental examination of a magnetorheological (MR) damper control system with vibration energy harvesting using a specially engineered electronic unit (EU). Unlike a typical MR damper control system, which requires an external energy source, the developed system is powered exclusively by energy extracted from a vibrating structure (mechanical system with one-degree-of freedom) and processed through the EU. The work describes the structure and functions of the EU, presents the test rig and the control algorithm implementation, and discusses the test results of the control system under harmonic kinematic excitations of low frequency range.

13

Optimal docking problem of UAV at detected moving object

Nabadova Lamiya

Zeszyty Naukowe. Transport / Politechnika Śląska

|

2023

|

z. 120

205--214

EN

In the article, the problem of detecting a suspicious object in the control by unmanned air vehicle (UAV) and tracking it by reaching and changing its direction in the shortest period of time is explored. To solve this optimal control problem, it is considered that the flight of UAV is described with simple motion equations. In the beginning, known quantities are current coordinates and speed of UAV, equation of motion of detected suspicious object.

14

Prediction of ship's speed through ground using the previous voyage's drift speed

Yamane D., Kano T.

TransNav : International Journal on Marine Navigation and Safety of Sea Transportation

|

2023

|

Vol. 17 No. 1

129--137

EN

In recent years, 'weather routing' has been attracting increasing attention as a means of reducing costs and environmental impact. In order to achieve high-quality weather routing, it is important to accurately predict the ship's speed through ground during a voyage from ship control variables and predicted data on weather and sea conditions. Because sea condition forecasts are difficult to produce in-house, external data is often used, but there is a problem that the accuracy of sea condition forecasts is not sufficient and it is impossible to improve the accuracy of the forecasts because the data is external. In this study, we propose a machine learning method for predicting speed through ground by considering the actual values of the previous voyage’s drift speed for ships that regularly operate on the same route, such as ferries. Experimental results showed that this method improves the prediction performance of ship’s speed through ground.

15

Neural approach for rhyming word recommendations

Borowska Aleksandra, Kosakowska Natalia, Samuel Szurman

TASK Quarterly : scientific bulletin of Academic Computer Centre in Gdansk

|

2023

|

Vol. 27, No 3

1--9

EN

This research paper deals with the problem of rhyme generation. The project concerns words in the Polish language. Two methods have been proposed to determine whether two words rhyme. A proprietary algorithm was created and three types of neural networks were trained. The efficiency of the methods and the way each of the discussed methods works was compared.

16

Information transfer with adaptation to the parameters of the communication channel

Kupchuk Ihor, Voznyak Oleksandr, Burlaka Serhiy, Polievoda Yurii, Vovk Valeriia, Telekalo Natalia, Hontaruk Yaroslav

Przegląd Elektrotechniczny

|

2023

|

R. 99, nr 3

194--199

EN

A variety of adaptation algorithms for the data transfer are proposed in order to select the optimal modes under difficult communication conditions. The performed calculations showed the efficiency of using the developed methods for adapting the information transfer device to the parameters of the communication channel. The results of the experimental verification of the work of adaptation algorithms showed the adequacy of theoretical studies with a deviation within 25%.

PL

Zaproponowano różnorodne algorytmy adaptacyjne przesyłania danych w celu doboru optymalnych trybów w trudnych warunkach komunikacyjnych. Przeprowadzone obliczenia wykazały skuteczność wykorzystania opracowanych metod dostosowania urządzenia przekazującego informacje do parametrów kanału komunikacyjnego. Wyniki eksperymentalnej weryfikacji działania algorytmów adaptacyjnych wykazały adekwatność badań teoretycznych z odchyleniem w granicach 25%.

17

Maszyna Turinga - podstawy działania i programowania

Gawryś Katarzyna

MINUT Matematyka i Informatyka na Uczelniach Technicznych

|

2023

|

Nr 5

264-272

PL

Maszyna Turinga jest opracowanym przez Alana Turinga ideowym modelem programowania. Ten abstrakcyjny model urządzenia służył do zapisu i wykonania algorytmów. Niniejszy artykuł opisuje budowę i sposób działania maszyny Turinga oraz zasady zapisu algorytmów w postaci tabeli przejść. W artykule umieszczono przykład użycia symulatora maszyny Turinga do rozwiązania przykładowego zadania. Analiza zamieszczonego przykładu, pozwoli odbiorcy, na przyswojenie sposobu szukania rozwiązania problemu, dla ideowego modelu komputera, jakim jest maszyna Turinga.

18

Innovative stress analysis and machine learning forecasting for semi-trailer truck body durability

Lyashuk Oleh, Levkovych Mykhailo, Stashkiv Mykola, Pastukh Oleh, Martyniuk Volodymyr, Mironov Dmytro, Rabe Marcin, Vovk Yuriy

Journal of Sustainable Development of Transport and Logistics

|

2023

|

Vol. 8, No. 2

43--57

EN

This article presents an in-depth analysis of the stress-deformation state (SDS) in the bottom structure of a semi-trailer truck body. Engineering analysis was conducted utilizing the SolidWorks software, focusing on a comprehensive CAD model of the semi-trailer truck body. The study explored variations in SDS parameters resulting from alterations in the geometric parameters of the body bottom elements. The research investigated alterations in static stress and displacement relative to changes in the proportions of the cross-section of the channel while maintaining fixed geometric dimensions of the workpiece, thickness of the workpiece, and the material of the body bottom. Graphical representations were generated to illustrate the variations in static stress, displacement, and safety margin concerning the thickness of the shelf and channel. Additionally, dependencies were derived that correlate static stresses in the channel with the thickness of the channel wall and the thickness of the body bottom sheet. The study results were compiled and summarized, offering valuable insights into the stress-deformation state of the semi-trailer truck body's bottom. Furthermore, machine learning techniques, specifically the RandomForest algorithm, were implemented in a Python environment to predict changes in static stress based on various factors. The model's predictions were validated by comparing predicted static stress values with actual values on a test sample. These findings facilitate efficient selection of appropriately sized elements by predicting static stress values, employing the RandomForest machine learning algorithm.

19

Advanced cascaded scheduling for highly autonomous production cells with material flow and tool lifetime consideration using AGVs

Miller Eddi, Engelmann Bastian, Kaupp Tobias, Schmitt Jan

Journal of Machine Engineering

|

2023

|

Vol. 23, No. 3

69--85

EN

In today’s manufacturing systems, especially in Industry 4.0, highly autonomous production cells play an important role. To reach this goal of autonomy, different technologies like industrial robots, machine tools, and automated guided vehicles (AGV) are deployed simultaneously which creates numerous challenges on various automation levels. One of those challenges regards the scheduling of all applied resources and their corresponding tasks. Combining data from a real production environment and Constraint Programming (CP-SAT), we provide a cascaded scheduling approach that plans production orders for machine tools to minimize makespan and tool changeover time while enabling the corresponding robot for robot-collaborated processes. Simultaneously, AGVs provide all production cells with the necessary material and tools. Hereby, magazine capacity for raw material as well as finished parts and tool service life are taken into account.

20

Determining the Correction Factors of Overhead-Conductors in 6kV Mining System of QuangNinh, VietNam with the Consideration of Power Harmonic Impact

Giang Vu Hoang, Thanh Le Xuan

Inżynieria Mineralna

|

2023

|

no. 2, vol. 1

71--78

EN

Understanding the impact of power harmonic on energy transmission play an important role not only in the operation process but also in the designing procedure of MV grid. In 6kV mining grids of Vietnamese coal mines, because of rapidly utilizing the power electronic machines, the power quality violation occurs very frequently. This lead to many disadvantages such as: the increase of power losses, voltage distortion, over-heating in transformers and conductors. Moreover, the presence of power harmonic bring the bad impact of skin effect and proximity on conductor including overhead-conductors and cables. The actual operation exhibits that the losses of transmission lines are approximately over 50% of total network losses. If there are power quality violation, this amount could be higher. Basing on investigating the fact of power harmonic violations in 6kV grid of both underground and surface mines, the paper will analyze this kind of impact. An algorithm relying on Matlab programming is used to calculate the energy losses. Results are compared with on-site measurement datas and lab-measurement to obtain series of correction factors corresponding to individual line’s cross section. The outcomes of research could be applicable for power utilities to have better analysis in the designing stage of mining MV grids.