About
24
Publications
2,547
Reads
How we measure 'reads'
A 'read' is counted each time someone views a publication summary (such as the title, abstract, and list of authors), clicks on a figure, or views or downloads the full-text. Learn more
99
Citations
Introduction
Juan Paulo Sanchez currently works at the Posgrado, Universidad Politécnica del Estado de Morelos.
Current institution
Publications
Publications (24)
The forecasting problem is vital in many areas, such as Energy, industry, financial series, and climate change. In forecasting, an ensemble is a combination of methods with different approaches. In other words, selecting only neural networks in an ensemble is not advisable because the advantages of various strategies are not exploited. This chapter...
This paper presents FORSEER (Forecasting by Selective Ensemble Estimation and Reconstruction), a novel methodology designed to address temperature forecasting under the challenges inherent to climate change. FORSEER integrates decomposition, forecasting, and ensemble methods within a modular framework. This methodology decomposes the time series in...
Accurate forecasting remains a challenge, even with advanced techniques like deep learning (DL), ARIMA, and Holt–Winters (H&W), particularly for chaotic phenomena such as those observed in several areas, such as COVID-19, energy, and financial time series. Addressing this, we introduce a Forecasting Method with Filters and Residual Analysis (FMFRA)...
Ionic liquids (ILs) are salts with a wide liquid temperature range and low melting points and can be fine-tuned to have specific physicochemical properties by the selection of their anion and cation. However, having a physical synthesis of multiple ILs for testing purposes can be expensive. For this reason, an in-silico estimation of physicochemica...
Computer vision methodologies using machine learning techniques usually consist of the following phases: pre-processing, segmentation, feature extraction, selection of relevant variables, classification, and evaluation. In this work, a methodology for object recognition is proposed. The methodology is called PSEV-BF (pre-segmentation and enhanced v...
Proteins are macromolecules essential for living organisms. However, to perform their function, proteins need to achieve their Native Structure (NS). The NS is reached fast in nature. By contrast, in silico, it is obtained by solving the Protein Folding problem (PFP) which currently has a long execution time. PFP is computationally an NP-hard probl...
La agricultura es considerada como una de las actividades que más impacta en la economía de los países. Por tal motivo, es de suma importancia atender los problemas que ésta enfrenta, entre los que destaca el control de enfermedades y plagas en los cultivos. Si este problema no es atendido se pueden presentar efectos graves en las plantas que afect...
The Protein Folding Problem (PFP) is a big challenge that has remained unsolved for more than fifty years. This problem consists of obtaining the tertiary structure or Native Structure (NS) of a protein knowing its amino acid sequence. The computational methodologies applied to this problem are classified into two groups, known as Template-Based Mo...
The COVID-19 disease constitutes a global health contingency. This disease has left millions people infected, and its spread has dramatically increased. This study proposes a new method based on a Convolutional Neural Network (CNN) and temporal Component Transformation (CT) called CNN–CT. This method is applied to confirmed cases of COVID-19 in the...
The Job Shop Scheduling Problem (JSSP) has enormous industrial applicability. This problem refers to a set of jobs that should be processed in a specific order using a set of machines. For the single-objective optimization JSSP problem, Simulated Annealing is among the best algorithms. However, in Multi-Objective JSSP (MOJSSP), these algorithms hav...
We know that SARS-Cov2 produces the new COVID-19 disease, which is one of the most dangerous pandemics of modern times. This pandemic has critical health and economic consequences, and even the health services of the large, powerful nations may be saturated. Thus, forecasting the number of infected persons in any country is essential for controllin...
We know that SARS-Cov2 produces the new COVID-19 disease, which is one of the most dangerous pandemics of modern times. This pandemic has critical health and economic consequences, and even the health services of the large, powerful nations may be saturated. Thus, forecasting the number of infected persons in any country is essential for controllin...
This paper proposes a hybrid method integrating case-based reasoning (CBR) and analytic hierarchy process (AHP) methods to reinforce the sustainable performance of an environmental management system. The CBR–AHP method aims to support the decision-making process to select environmental management actions (EMAs) aimed at reducing risky trends of the...
This paper proposes a Case-Based Reasoning (CBR) system to contribute to reinforce the sustainable performance of an environmental management system. The CBR system aims to support the decision-making process to select environmental management actions aimed at reducing risky trends of the environmental state of a region. The CBR system takes advant...
Protein Folding Problem (PFP) is one of the most challenging problems of combinatorial optimization with applications in bioinformatics and molecular biology. The aim of PFP is to find the three-dimensional structure of a protein, this structure is known as Native Structure (NS), which is characterized by the minimal energy of Gibbs and it is commo...
En este artículo, se presenta una aplicación desarrollada en la plataforma Android que permite el diagnóstico de melanoma maligno. Las características clínicas utilizadas para realizar el diagnóstico del melanoma maligno están basadas en: Asimetría, Borde, Color y Diámetro o regla ABCD de la lesión cutánea. En este trabajo se toma en consideración...
A new hybrid Multiphase Simulated Annealing Algorithm using Boltzmann and Bose-Einstein distributions (MPSABBE) is proposed. MPSABBE was designed for solving the Protein Folding Problem (PFP) instances. This new approach has four phases: (i) Multiquenching Phase (MQP), (ii) Boltzmann Annealing Phase (BAP), (iii) Bose-Einstein Annealing Phase (BEAP)...
In this paper, Golden Ratio Simulated Annealing (GRSA) for Protein Folding Problem (PFP) is presented. GRSA is similar to Multiquenching Annealing (MQA) and Threshold Temperature Simulated Annealing (TTSA) algorithms. In contrast to MQA and TTSA, GRSA uses several strategies in order to reduce the execution time for finding the best solution of PFP...
Las características físicas externas de un melanoma maligno, tales como su asimetría, color, diámetro y borde, permiten identificarlo y diferenciarlo de una lesión común o melanoma benigno sin necesidad de recurrir a una biopsia. En este trabajo se presentan una metodología y una comparación de resultados obtenidos mediante las redes neuronales art...
The Chaotic Multiquenching Annealing algorithm (CMQA) is proposed. CMQA is a new algorithm, which is applied to protein folding problem (PFP). This algorithm is divided into three phases: (i) multiquenching phase (MQP), (ii) annealing phase (AP), and (iii) dynamical equilibrium phase (DEP). MQP enforces several stages of quick quenching processes t...
In this paper, Threshold Temperature Simulated Annealing algorithm (TTSA) is presented. TTSA is an algorithm based on the classical Simulated Annealing Algorithm (SA) and a reheat technique. This algorithm was devised for the problem known as Protein Folding Problem (PFP) in small peptides. A quality threshold temperature is introduced in the paper...
A ubiquity system has pervasive features with certain intelligence level. On the other hand, ubiquity means the existence or apparent existence, everywhere or at the same time. In nowadays, ubiquity is becoming the most import features for web developments, especially in education area. In this paper, a Ubiquity Collaborative Architecture (UCAT) fo...
In this paper, an improved Simulated Annealing algorithm for Protein Fold-ing Problem (PFP) is presented. This algorithm called Cluster Perturbation Simulated Annealing (CPSA) is based on a brand new scheme to generate new solutions using a cluster perturbation. The algorithm is divided into two phases: Cluster Perturbation Phase and the Reheat Pha...
