A study on variations of Genetic Programming applied to time series forecasting: Machine Learning for Energy Consumption Forecasting

Dissertation presented as the partial requirement for obtaining a Master's degree in Data Science and Advanced Analytics, specialization in Data ScienceEvolutionary Computation is a sub-field of Machine Learning algorithms based on Darwin’s theory of Evolution. Individuals are evolved using the principles of mutation, crossover and natural selection. One of the most known Evolutionary Algorithms is Genetic Programming (GP), that evolves as individuals computer programs in order to solve regression problems. In this thesis two variations of GP, namely Geometric Semantic Genetic Programming(GSGP) and Tree-based Pipeline Optimization Tool(TPOT), are applied to two energy consumption time series regression problems. Their performance are then compared to state-of-the-art models, LSTM and SVR optimized with DE, and to standard GP. It is showed that the variations of GP outperform standard GP and SVR optimized with DE, while also having comparable performance to LSTM. Additionally a study on the feature selection ability of GSGP is proposed, showing that the algorithm is not actually able to perform feature selection

A Study of Dynamic Populations in Geometric Semantic Genetic Programming

Farinati, D., Bakurov, I., & Vanneschi, L. (2023). A Study of Dynamic Populations in Geometric Semantic Genetic Programming. Information Sciences, 648(November), 1-21. [119513]. https://doi.org/10.1016/j.ins.2023.119513 --- This work was supported by national funds through FCT (Fundação para a Ciência e a Tecnologia), under the project - UIDB/04152/2020 - Centro de Investigação em Gestão de Informação (MagIC)/NOVA IMS.Allowing the population size to variate during the evolution can bring advantages to evolutionary algorithms (EAs), retaining computational effort during the evolution process. Dynamic populations use computational resources wisely in several types of EAs, including genetic programming. However, so far, a thorough study on the use of dynamic populations in Geometric Semantic Genetic Programming (GSGP) is missing. Still, GSGP is a resource-greedy algorithm, and the use of dynamic populations seems appropriate. This paper adapts algorithms to GSGP to manage dynamic populations that were successful for other types of EAs and introduces two novel algorithms. The novel algorithms exploit the concept of semantic neighbourhood. These methods are assessed and compared through a set of eight regression problems. The results indicate that the algorithms outperform standard GSGP, confirming the suitability of dynamic populations for GSGP. Interestingly, the novel algorithms that use semantic neighbourhood to manage variation in population size are particularly effective in generating robust models even for the most difficult of the studied test problems.publishersversionpublishe

Simplifying fitness landscapes using dilation functions evolved with genetic programming

Several optimization problems have features that hinder the capabilities of searching heuristics. To cope with this issue, different methods have been proposed to manipulate search spaces and improve the optimization process. This paper focuses on Dilation Functions (DFs), which are one of the most promising techniques to manipulate the fitness landscape, by "expanding " or "compressing " specific regions. The definition of appropriate DFs is problem dependent and requires a-priori knowledge of the optimization problem. Therefore, it is essential to introduce an automatic and efficient strategy to identify optimal DFs. With this aim, we propose a novel method based on Genetic Programming, named GP4DFs, which is capable of evolving effective DFs. GP4DFs identifies optimal dilations, where a specific DF is applied to each dimension of the search space. Moreover, thanks to a knowledge-driven initialization strategy, GP4DFs converges to better solutions with a reduced number of fitness evaluations, compared to the state-of-the-art approaches. The performance of GP4DFs is assessed on a set of 43 benchmark functions mimicking several features of real-world optimization problems. The obtained results indicate the suitability of the generated DFs

Laparoscopic ablation of hepatocellular carcinoma in cirrhotic patients unsuitable for liver resection or percutaneous treatment: a cohort study.

The aim of this study was to demonstrate the safety and efficacy of laparoscopic ablation for cirrhotic HCC patients. Between January 2004 and December 2009, laparoscopic ablation was applied prospectively in 169 consecutive HCC patients (median age 62 years, 43% hepatitis C positive) considered ineligible for liver resection and/or percutaneous ablation. There was clinically relevant portal hypertension in 72% of cases. A significant proportion of subjects (50%) had multinodular tumors or nodules larger than 25 mm. The main ablation techniques used were radiofrequency in 103 patients (61%), microwave ablation in 8 (5%), and ethanol injection in 58 (34%). The primary endpoint was 3-year survival. There was no perioperative mortality. The overall morbidity rate was 25%. The median postoperative hospital stay was 3 days (range 1-19 days). Patients survived a median 33 months with a 3-year survival rate of 47%. Cox's multivariate analysis identified patient age, presence of diabetes, albumin ≤37 g/l, and alpha-fetoprotein >400 µg/l as significant preoperative predictors of survival, while the chance to undergo liver transplantation and postoperative ascites were the only independent postoperative predictor of survival. Laparoscopic ablation is a safe and effective therapeutic option for selected HCC patients ineligible for liver resection and/or percutaneous ablation

Systemic therapies for hepatocellular carcinoma: a recap of the current status

After decades of frustrating nihilism due to lack of innovative therapeutic solutions, the onco-hepatological community is facing up to important novelties for the treatment of intermediate and advanced stages of liver cancer. Four new drugs have been investigated and resulted in positive data: lenvatinib resulted not inferior to the standard of care sorafenib in first line, regorafenib and cabozantinib demonstrated prolonging survival in patients progressed to sorafenib and nivolumab approved by FDA as option after first-line. Contemporary, the knowledge acquired after ten years’ experience of sorafenib in patient selection and adverse events management revealed an increase of the outcomes. Physicians dedicated to treat advanced and intermediated liver cancer are close to live a new era where systemic treatments could have a huge impact on the disease. The aim of this review is to anticipate this new approach at the disease, summarizing data currently available for these therapies to identify therapeutic strategies of sequences and choosing drugs according to the patient profile

Laparoscopic Ablation of Hepatocellular Carcinoma in Cirrhotic Patients Unsuitable for Liver Resection or Percutaneous Treatment: A Cohort Study

The aim of this study was to demonstrate the safety and efficacy of laparoscopic ablation for cirrhotic HCC patients. Between January 2004 and December 2009, laparoscopic ablation was applied prospectively in 169 consecutive HCC patients (median age 62 years, 43% hepatitis C positive) considered ineligible for liver resection and/or percutaneous ablation. There was clinically relevant portal hypertension in 72% of cases. A significant proportion of subjects (50%) had multinodular tumors or nodules larger than 25 mm. The main ablation techniques used were radiofrequency in 103 patients (61%), microwave ablation in 8 (5%), and ethanol injection in 58 (34%). The primary endpoint was 3-year survival. There was no perioperative mortality. The overall morbidity rate was 25%. The median postoperative hospital stay was 3 days (range 1-19 days). Patients survived a median 33 months with a 3-year survival rate of 47%. Cox's multivariate analysis identified patient age, presence of diabetes, albumin 6437 g/l, and alpha-fetoprotein >400 \ub5g/l as significant preoperative predictors of survival, while the chance to undergo liver transplantation and postoperative ascites were the only independent postoperative predictor of survival. Laparoscopic ablation is a safe and effective therapeutic option for selected HCC patients ineligible for liver resection and/or percutaneous ablation

Survival according to possibility to have liver transplantation after LA (p = 0.0004).

<p>Survival according to possibility to have liver transplantation after LA (p = 0.0004).</p

Multivariate survival analyses.

1<p>leakage from abdominal drains >1000 ml/day.</p><p>ASA, American Society of Anesthesiologists physical status score; BCLC, Barcelona Clinic liver cancer stage.</p

Clinicopathological characteristics.

<p>ASA, American Society of Anesthesiologists physical status score; HCV, hepatitis C virus; HBV, hepatitis B virus; MELD, model end-stage liver disease score; HCC, hepatocellular carcinoma; BCLC, Barcelona Clinic liver cancer stage; RF, radiofrequency; MW, microwave.</p

Kaplan-Meier survival curves by BCLC stage (p>0.05).

<p>Kaplan-Meier survival curves by BCLC stage (p>0.05).</p