Analyzing the opinions and emotions of Internet customers using deep ensemble learning based on rbm

Background: The emotions and opinions of Internet users are critical, as they directly influence the provision of proper services. The aim of this study was analyzing the opinions and emotions of internet customers using deep ensemble learning based on rbm. Methods: Method of this study was based on the deep ensemble learning technique which uses a deep ensemble neural network based on Gaussian restricted Boltzmann machine and cost-sensitive tree the opinions and emotions of Internet customers were analyzed in terms of semantics and linguistics in virtual shops. To analyze behavior or emotions, existing algorithms were divided into groups of semantic approach, language approach and machine learning. The semantic, linguistic and group learning aspects (machine learning) were considered together. The opinions, feelings, and behaviors of Internet customers were analyzed. The proposed method was implemented in MATLAB software. To evaluate this method, conventional criteria that were /applied in data mining applications have been used including accuracy, recall, and F score. Results: Based on the experiments performed and by evaluating this method against individual and ensemble methods plus the approaches presented in data mining so far, it was revealed that the proposed model outperforms other methods regarding data mining assessment criteria. Conclusion: Based on social engineering, the suggested model is provided to forecast consumer behavior. In addition to analyzing customers' behavior which examined their emotions and feelings based on their opinions. The results of this study can be used by planners in the field of competitive internet markets

A study on the personalization methods of the web

Search engine personalization is one of the various deep personalization methods. It can be said that personalization systems that help users find the information they need requires the use of contextual and semantic information analysis techniques that exist in the field of data recovery such as web personalization and the process of optimizing the methods to get to web pages in a way that are consistent with the needs of each user. What helps the current problem of search engines and accelerate their performance, is providing a proper framework for finding the correct pattern considering great items in history of users. This approach improves the advising process of the search engines as well. The aim of this paper is to introduce some process improvement methods of correct patterns and analyze them. Here we will discuss the basic concepts of web personalization and consider the three approaches of web personalization and we evaluated the methods belonging to each of them.Keywords: personalization, search engine, user preferences, data mining method

Power loss due to soiling on solar panel: a review

The power output delivered from a photovoltaic module highly depends on the amount of irradiance, which reaches the solar cells. Many factors determine the ideal output or optimum yield in a photovoltaic module. However, the environment is one of the contributing parameters which directly affect the photovoltaic performance. The authors review and evaluate key contributions to the understanding, performance effects, and mitigation of power loss due to soiling on a solar panel. Electrical characteristics of PV (Voltage and current) are discussed with respect to shading due to soiling. Shading due to soiling is divided in two categories, namely, soft shading such as air pollution, and hard shading which occurs when a solid such as accumulated dust blocks the sunlight. The result shows that soft shading affects the current provided by the PV module, but the voltage remains the same. In hard shading, the performance of the PV module depends on whether some cells are shaded or all cells of the PV module are shaded. If some cells are shaded, then as long as the unshaded cells receive solar irradiance, there will be some output although there will be a decrease in the voltage output of the PV module. This study also present a few cleaning method to prevent from dust accumulation on the surface of solar arrays

Comparison of developed FLC and P&O MPPT algorithms for improving PV system performance at variable irradiance conditions

Purpose: This work aims to overcome the drawbacks of the nonlinear characteristics of the photo-voltaic (PV) system which are affected by the atmospheric variations. Design/methodology/approach: As a result, the optimum power point on these characteristics accordingly changes and the efficiency of photovoltaic systems reduces. Maximum power point tracking (MPPT) algorithms track this optimum point and enhance the efficiency despite the irradiance and temperature changes. Findings: The conventional perturbation and observation (P&O) algorithm uses fixed step sizes to increment and decrement the duty ratio that leads to slow response time and continuous oscillation around the MPP at steady state conditions. The paper proposes a fuzzy logic-based controller that overcomes the drawbacks of P&O algorithm in term of response time and the oscillation. Originality/value: MATLAB/Simulink environment was used to model and simulate the KC200GT PV module, direct current (DC)-DC boost converter and the MPPT algorithms

DC-DC converter for photovoltaic powered battery charger

Purpose: The purpose of this study is to show in power-voltage curve, a unique maximum power point (MPP) is existed which has the maximum power. Design/methodology/approach: This paper presents a MPP tracker algorithm for a standalone system includes DC-DC buck converter and battery storage. Findings: By using this algorithm, the maximum available power is achieved and simultaneously, the battery is charged and also protected against overcharge and discharge. The operation of the proposed algorithm is evaluated in with Proteus software to be sure that it can be implemented in microcontroller in reality. Originality/value: The simulations results show that the proposed algorithm is able to detect the MPP under different irradiations. Moreover, the battery is charged during the day by PV and protected against overcharge and discharge

Novel hybrid maximum power point tracking algorithm for PV systems under partially shaded conditions

Photovoltaic (PV) system has non-linear powervoltage (P-V) characteristic with single maximum power point (MPP) in uniform condition. The P-V curve would be more complicated during partially shaded (PS) conditions (PSCs) when multi-peak powers exist. The point with the highest value of power among the multi-peak powers is called global maximum power point (GMPP). In this paper, a novel hybrid method is proposed to obtain the GMPP in PSCs. In this method, if PS happens after reaching the MPP in uniform condition, the new operating point is specified based on modified linear function to reduce the searching zone and simultaneously the possible MPPs are recognized at the right side of the new obtained operating point. In the case where PS happens before reaching the MPP in uniform condition, the reference point is specified and then the location of GMPP is detected. Finally, after specifying the exact location of GMPP, the modified P&O is used to obtain the GMPP. To evaluate operation of the proposed method, simulation work has been carried out in MATLAB/Simulink where the GMPP is obtained in minimum time with high accuracy and minimum oscillation in power. Moreover, this method is not limited to any specific scenarios of shadowing

Evaluation of Fuzzy Logic Subsets Effects on Maximum Power Point Tracking for Photovoltaic System

Photovoltaic system (PV) has nonlinear characteristics which are affected by changing the climate conditions and, in these characteristics, there is an operating point in which the maximum available power of PV is obtained. Fuzzy logic controller (FLC) is the artificial intelligent based maximum power point tracking (MPPT) method for obtaining the maximum power point (MPP). In this method, defining the logical rule and specific range of membership function has the significant effect on achieving the best and desirable results. This paper presents a detailed comparative survey of five general and main fuzzy logic subsets used for FLC technique in DC-DC boost converter. These rules and specific range of membership functions are implemented in the same system and the best fuzzy subset is obtained from the simulation results carried out in MATLAB. The proposed subset is able to track the maximum power point in minimum time with small oscillations and the highest system efficiency (95.7%). This investigation provides valuable results for all users who want to implement the reliable fuzzy logic subset for their works

Nitro group reduction and Suzuki reaction catalysed by palladium supported on magnetic nanoparticles modified with carbon quantum dots generated from glycerol and urea

Glycerol and urea were used as green and cheap sources of carbon quantum dots (CQD) for modifying Fe3O4 nanoparticles (NPs). The obtained CQD@Fe3O4 NPs were used for the stabilization of palladium species and the prepared catalyst, Pd@CQD@Fe3O4, was characterized using various techniques. This magnetic supported palladium was applied as an efficient catalyst for the reduction of aromatic nitro compounds to primary amines at room temperature using very low palladium loading (0.008 mol%) and also for the Suzuki–Miyaura cross-coupling reaction of aryl halides as well as challenging heteroaryl bromides and aryl diazonium salts with arylboronic acids and with potassium phenyltrifluoroborate. This magnetically recyclable catalyst was recovered and reused for seven consecutive runs in the reduction of 4-nitrotoluene to p-toluidine and for ten consecutive runs in the reaction of 4-iodoanisole with phenylboronic acid with small decrease of activity. The catalyst reused in the Suzuki reaction was characterized using transmission electron microscopy, vibrating sample magnetometry and X-ray photoelectron spectroscopy. Using experiments such as hot filtration and poisoning tests, it has been shown that the true catalyst works under homogeneous conditions according to the release–return pathway of active palladium species.Iran National Science Foundation, Grant/Award Number: 95844587; the Generalitat Valenciana, Grant/Award Number: PROMETEOII/2014/017; the Spanish Ministerio de Economía, Industria y Competitividad, Agencia Estatal de Investigación (AEI) and Fondo Europeo de Desarrollo Regional (FEDER, EU), Grant/Award Number: CTQ2016‐81797‐REDC and CTQ2016‐76782‐P; the Spanish Ministerio de Economía y Competitividad (MINECO), Grant/Award Number: CTQ2014‐51912‐REDC and CTQ2013‐43446‐P

Implementing a Novel Hybrid Maximum Power Point Tracking Technique in DSP via Simulink/MATLAB under Partially Shaded Conditions

This paper presents a hybrid maximum power point tracking (MPPT) method to detect the global maximum power point (GMPP) under partially shaded conditions (PSCs), which have more complex characteristics with multiple peak power points. The hybrid method can track the GMPP when a partial shadow occurs either before or after acquiring the MPP under uniform conditions. When PS occurs after obtaining the MPP during uniform conditions, the new operating point should be specified by the modified linear function, which reduces the searching zone of the GMPP and has a significant effect on reducing the reaching time of the GMPP. Simultaneously, the possible MPPs are scanned and stored when shifting the operating point to a new reference voltage. Finally, after determining the possible location of the GMPP, the GMPP is obtained using the modified P&O. Conversely, when PS occurs before obtaining the MPP, the referenced MPP should be specified. Thus, after recognizing the possible location of the GMPP, the modified P&O can be used to obtain the GMPP. The simulation and experimental implementations for the proposed algorithm are performed with different scenarios of shadowing under different irradiations, which clearly indicate that the proposed method is robust and has a fast tracking speed. Moreover, this work presents the load sizing method for PSCs to avoid controller failure when detecting the GMPP. Additionally, in this paper, the user-friendly method for programming the digital signal processing (DSP) via Simulink/MATLAB is presented in detail

Dual search maximum power point algorithm based on mathematical analysis under partially-shaded conditions

Solar energy has drawn much attention in recent years because of high demand for green energy resources. Electrical power can be generated by using semiconductors in photovoltaic (PV) cells to convert solar irradiance into DC current. Each PV module has its own optimum point at which the power delivered from the PV is at its maximum value. Since the initial cost for using PV is high, it is essential to make the PV module to operate at its maximum power point (MPP). However, the non-linear relation between current and voltage for the PV system is a challengeable issue that results in a unique MPP for its power-voltage (P-V) curve. Under uniform conditions or without shading, there is a unique MPP on the P-V curve. By changing the irradiance and temperature, the value of MPP will be changed. The PV system is troubled with the weakness of nonlinearity between current and voltage under partially shaded conditions PSCs). Under PSCs, there are multi-peak powers. Only one of these peak powers has the highest power, which is called global maximum power point (GMPP), and other peak powers are the local maximum power point (LMPP).The maximum power point tracking (MPPT) algorithms under PSCs can be categorized generally in two groups. In the first group, the conventional techniques are combined with other techniques and the second group is based on the optimization methods. One of the main challenges of MPPT techniques under PSCs is ability of the algorithms to find the GMPP faster with minimal oscillation in power. Moreover, it is very important that the algorithms should be general and not so complicated which could be implemented for all systems.Therefore, this research presents design and development of a novel method, which is called dual search maximum power point (DSMPP) algorithm, for tracking the GMPP under PSCs. The proposed method is based on mathematical analysis that reduces the search zone and simultaneously identifies the possible MPPs in the specified zone that leads to determining the GMPP in minimum time. In this work, the perturb and observation (P&O) method based on duty cycle adjustment is introduced, which is modified to increase speed of the search and also to reduce the oscillation.The simulation and experimental works have been performed to investigate behavior and performance of the proposed algorithm. The PV array in series-parallel (SP)configuration is considered as an input of the standalone system and mathematical model of this PV array under PSC has been developed. Moreover, the load sizing method for PSCs is also presented to avoid controller failure when detecting the GMPP. In evaluation part, the DSMPP algorithm has been compared with two other methods.According to both simulation and experimental results, by implementing the DSMPP technique, the GMPP can be obtained faster. Moreover, the oscillation in power is reduced significantly. Interestingly, the experimental results under different irradiances also show that the proposed algorithm can detect the GMPP faster in comparison with other methods. The significant reduction of oscillation in power is observed to be due to implementation of the modified P&O.As a conclusion, the DSMPP algorithm has successfully been performed to detect the GMPP under PSCs in minimum time, with low oscillation in power, and high accuracy as detecting the GMPP for different scenarios of shadowing