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El presente trabajo de investigación tiene como objetivo aplicar técnicas de análisis de regresión y aprendizaje automático (ML) para mejorar los resultados de estimación de sobre dilución en tajos explotados por el método de Sub Level Stoping (SLS) de la Compañía Minera Condestable (CMC) a través de la generación de ecuaciones de regresión y código en lenguaje de Python para las técnicas de ML. Para la estimación de sobre dilución se analizaron las reconciliaciones de tajos explotados con el método de SLS del período 2017-2019 con la aplicación de las técnicas: Análisis de Regresión Lineal Múltiple (ARLM), regresión no lineal múltiple (ARNM) y métodos de aprendizaje automático (ML) como Máquinas de Vectores de Soporte (SVM) y bosques aleatorios (RF), lo que permitió establecer comparaciones entre los resultados a nivel predictivo y tecnológico con la metodología de O’Hara aplicada actualmente en CMC para la estimación de sobre dilución de tajos SLS. La aplicación de las técnicas mencionadas implicó variables operativas como: nivel, buzamiento, densidad, burden, espaciamiento, altura, longitud, ancho, RQD, RMR y ratio de tonelada por metro de perforación (TMP) de los tajos evaluados, mientras que el objetivo o variable dependiente fue la sobre dilución. Ello permitió inicialmente identificar que las técnicas de regresión ARLM y ARNM mejoraron el coeficiente de determinación R2 de O’Hara en 5.5% y 4.4%. Luego, con la aplicación de herramientas de aprendizaje automático se identificó que ambas técnicas (SVM y RF) lograron la mejora en 0.3% y 18.5% respectivamente. El resultado de ello fue la reducción de la diferencia de costos estimados obtenidos con la metodología de O’Hara relacionados al costo adicional por carguío y transporte de carga rota de dilución. / This research work aims to apply Regression Analysis and Machine Learning (ML) techniques to improve the results of estimating over dilution in stopes mined by Sub Level Stoping (SLS) method at Compania Minera Condestable (CMC) through the generation of regression equations and code in Python language for ML techniques. For the estimation of over dilution, the reconciliations of stopes mined with the SLS method for the period 2017-2019 were analysed with the application of the techniques: Multiple Linear Regression Analysis (MLRA), Multiple Non-linear Regression Analysis (MLNRA) and Machine Learning (ML) methods such as Support Vector Machine (SVM) and Random Forests (RF), which allowed comparisons of the results at predictive and technological level with the O'Hara methodology currently applied at CMC for the estimation of over dilution of SLS stopes. The application of the afore mentioned techniques involved operational variables such as: level, dip, density, burden, spacing, height, length, width, RQD, RMR and tonne per metre drilling (TMP) ratio of the evaluated stopes, while the objective or dependent variable was over dilution. This initially identified that the ARLM and ARNM regression techniques improved O'Hara's R2 determination coefficient by 5.5% and 4.4%. Then, with the application of machine learning tools it was identified that both techniques (SVM and RF) achieved the improvement by 0.3% and 18.5% respectively. This resulted in a reduction of the estimated cost difference obtained with the O'Hara methodology related to the additional cost of loading and transporting broken stock from the dilution. / Tesis

El principal indicador para evaluar la calidad del suelo como subrasante en el diseño de pavimentos es la capacidad de soporte CBR. En muchos casos, no es posible su obtención mediante ensayos, al menos en la frecuencia requerida, y son muy costosos. Por ello, la necesidad de cuantificar este parámetro mediante modelos matemáticos que utilicen propiedades fácilmente determinables y permitan evaluar rápidamente la eficacia de una solución de estabilización. En el presente trabajo de investigación tiene como propósito desarrollar herramientas prácticas para la predicción del valor de CBR del suelo expansivo post estabilización con ceniza de cáscara de arroz (CCA) y cal. Se plantea obtener modelos matemáticos basados en la regresión lineal múltiple haciendo uso de sus propiedades índice (%F, IP) y de compactación (OCH, MDS), los cuales se generaron mediante la aplicación del software SPSS Statistics, cuya ecuación resultante fue: 〖CBR〗_f=46.116-0.526 %F+0.034 IP+0.218 OCH+5.06 MDS Esta ecuación presenta una correlación muy alta con R = 0.975 y un ajuste de bondad excelente de R2 = 0.95. Esto quiere decir que la variable de respuesta CBR es explicada en un 95% por las variables predictoras %F, IP, OCH y MDS. El modelo de regresión propuesto se aplicó a un tramo de la carretera PE-8B en la región San Martín donde se observó que el valor de CBR se incrementa en promedio 272% al estabilizarse con los agentes de estudio sugeridos. / The main indicator to evaluate the quality of the soil as a subgrade in pavement design is the California Bearing Ratio (CBR). In many cases, it is not possible to obtain them by testing, at least at the required frequency, and they are very expensive. Therefore, the need to quantify this parameter through mathematical models that use easily determinable properties and will evaluate the effectiveness of a proposed stabilization solution. The purpose of this research work is to develop practical tools for the prediction of the CBR in expansive soil post stabilization with rice husk ash and lime. It is proposed to obtain mathematical models based on multiple linear regression using their index (% F, IP) and compaction (OCH, MDS) properties, which were generated by applying the SPSS Statistics software, whose resulting equation was: 〖CBR〗_f=46.116-0.526 %F+0.034 IP+0.218 OCH+5.06 MDS, which presents a very high correlation with R = 0.975 and an excellent goodness fit of R2 = 0.95. This means that the CBR response variable is 95% explained by the predictor variables %F, IP, OCH and MDS. The proposed regression model was applied to a section of the PE-8B highway in the San Martín region where it was found that the CBR value was found on average 272% when stabilized with the suggested study materials. / Tesis

The purpose of this study was to determine the limiting nutrient in a set of coastal areas and estuaries in the Baltic Sea. Although the subject as been studied for several decades, no clear consensus has been reached in the scientific community as to whether primary production is limited by phosphorus or nitrogen. A total of five coastal areas, all located on the east coast of Sweden, were assessed regarding their limiting nutrient by using three methods. The first method was applying linear regression analysis on measured TP and TN concentration together with chlorophyll-a and Secchi depth. The data was collected from sampling programs stretching back to the 1970s and 80s, studying the summer period May to September for all sites but one, were the period April to October was studied. The second method calculated the TN/TP ratio during the summer period and compared it to the Redfield ratio. Thirdly, basic mass-balance calculations were carried out, with empirical data on the external loads and calibrated with the yearly average concentration in the surface water (0–10 m). From the calculations, both the annual external and internal load of TP and TN was obtained. The different TP and TN loads were likewise tested for a correlation with the measured summer chlorophyll-a concentration and Secchi depth. The results of using linear regression analysis on measured concentrations were mostly inconclusive, as the TP and TN concentrations for all sites and most years were related to each other. Consequently both nutrients often gave equal correlation coefficients. Similarly the TP and TN loads also matched each other for most sites and years, inherently obtaining the same inconclusive, but also contradictory results, as when using the measured concentrations. The TN/TP ratio indicated, for one site that it was limited by phosphorus and another site possibly nitrogen limitation. The ratio in the other sites periodically dropped between nitrogen and phosphorus limitation over the years. Thus it was difficult to draw an overall conclusion as to what nutrient was the limiting one for all the sites. However analysing the results from the individual sites showed that three of the five sites had signs of phosphorus limitation. Two factors were deemed as being the main reasons as to why the methods did not achieve more conclusive results. The first factor was the empirical data, which varied in frequency and extent over the studied time periods and between sites, making representative concentrations difficult to calculate and evaluate. The second was the matching trends between both the concentrations and the loads of TP and TN. To achieve a better result one nutrient could be increased or decreased while one remains relatively constant. The problem with such an experiment would be controlling the inflow of nutrients from the adjacent sea. / Syftet med detta projekt var att bestämma det begränsande näringsämnet för ett antal kustområden i Östersjön. Frågan huruvida fosfor eller kväve är det begränsande näringsämnet i kustområden runt Östersjön har varit omdiskuterad under flera år och undersökts vid ett flertal tillfällen. I denna studie testades tre metoder, i fem olika kustområden, med syftet att fastställa det begränsande näringsämnet. Först användes linjär regressionsanalys med uppmätta värden på TP och TN koncentrationer tillsammans med klorofyll-a och Secchidjup. Empirisk data insamlades från övervakningsprogram där prover tagits sedan 1970- och 80-talet. Medelvärden beräknades för perioden maj till september för alla områden förutom ett, där undersöktes perioden april till oktober. Sommarmedelvärdena för TN/TP kvoten analyserades också för alla områden med avseende på Redfield kvoten. Slutligen genomfördes massbalansberäkningar med data för de externa belastningarna av TP och TN, dessa beräkningar kalibrerades sedan med uppmätta värden på koncentrationen i ytvattnet (0–10 m). Utifrån beräkningarna erhölls värden på den externa och den interna belastningen. Dessa belastningar testades med linjär regression för ett samband med de uppmätta värdena på Secchidjup och klorofyll-a. Metoden att använda linjär regressionsanalys med empiriskt uppmätta koncentrationer och djup, gav generellt ett oklart resultat. Detta var en följd av att halterna av både TP och TN i regel följdes åt, vilket fick konsekvensen att korrelationskoefficienterna för TP och TN ofta var lika stora. Samma problem uppstod för regressionsanalysen med belastningarna, då även dessa ofta följde varandra, men även motsade resultatet med koncentrationerna. Analysen av TN/TP kvoten tydde på att ett område var fosforbegränsat och ett område möjligen var kvävebegränsat. För de övriga tre områdena skiftade TN/TP kvoten under åren mellan kväve- och fosforbegränsning. De oklara resultaten gjorde det svårt att dra en övergripande slutsats. Däremot vid analysen av de enskilda områdena uppvisade tre av de fem områdena tecken på fosforbegränsning, även om detta inte kunde med säkerhet fastställas. Det var huvudsakligen två faktorer vars inverkan anses ha haft stor betydelse för det oklara resultatet. Den första faktorn var uppmätt data, vars frekvens och omfattning skiljde sig avsevärt mellan år och platser. Följaktligen försvårades beräkningarna av koncentrationerna och tillförlitligheten i hur representativa värdena var. Den andra och avgörande faktorn var de matchande trenderna hos både koncentrationerna och belastningarna. För att förbättra resultatet kan ett näringsämne ändras, medan det andra näringsämnet hålls relativt konstant. Problemet med att genomföra ett sådant experiment skulle vara att kontrollera inflödet av näringsämnen från närliggande hav.

This work solves creation of calibration relations to determine cube compressive strength, dynamic and static elastic modulus of alkali-activated concrete by non-destructive methods. Alkali-activated concrete is spoken of as a new material used in civil engineering. It shows different properties than normal concrete based on Portland cement. That's why the modification of common calibration relation seems necessary. Fresh concrete was made in the concrete plan ŽPSV a.s., Uherský Ostroh in three mixtures and always in the number of 18 cubes and 3 prisms. The samples were tested by impact hammer Schmidt type L, type N, SilverSchmidt PC-N and by ultrasound in 6 time periods of three specimens. After that, the cube compressive strength was determined. Status of static elastic modulus was determined in a time period of 28 days. The results are calibration relations to determine the progress of compressive strength and modulus of elasticity for each method and their combination.