Abstract In today’s society, investment wealth management has become a mainstream of the contemporary era. Investment refers to use funds by investors arrange reasonably, for example, savings, bank financial products, bonds, stocks, commodity spots, real estate, gold, art, and many others. Wealth tools manage assign families, individuals, enterprises, institutions achieve purpose increasing maintaining value accelerate asset growth. Among them, in management, people’s favorite product often...

High-utility itemset mining is a popular data problem that considers utility factors, such as quantity and unit profit of items besides frequency measure from the transactional database. It helps to find most valuable profitable products/items are difficult track by using only frequent itemsets. An item might have high-profit value which rare in database has tremendous importance. While there many existing algorithms high-utility itemsets (HUIs) generate comparatively large candidate sets,...

In an era where people in the world are concerned about environmental issues, companies must reduce distribution costs while minimizing pollution generated during process. For today’s multi-depot problem, a mixed-integer programming model is proposed this paper to minimize all incurred entire transportation process, considering impact of time-varying speed, loading, and waiting time on costs. Time directional; hence, problems considered study modeled based asymmetry, making problem-solving...

Over the past decade, high-utility itemset mining (HUIM) has received widespread attention that can emphasize more critical information than was previously possible using frequent (FIM). Unfortunately, HUIM is very similar to FIM since methodology determines itemsets a binary model based on pre-defined minimum utility threshold. Additionally, most previous works only focused single, small datasets in HUIM, which not realistic any real-world scenarios today containing big data environments....

Abstract The stock market is a capitalistic haven where the issued shares are transferred, traded, and circulated. It bases prices on issue market, however, structure trading activities of much more complicated than itself. Therefore, making an accurate prediction becomes intricate as well highly difficult task. On other hand, because potential benefits prediction, it attracts generation after scholars investors to continuously develop various methods from different perspectives, myriad...

In recent years, privacy-preserving data mining (PPDM) has received a lot of attention in the field research. While some sensitive information databases cannot be revealed, PPDM can discover additional important knowledge and still hide critical information. There are different ways to approach this exhibited previous research, which applied addition deletion operations adjust an original database order However, it is NP-hard problem find appropriate set transactions/itemsets for hiding...

With the fast development of Industrial Internet Things (IIoT), IIoT storage, which provides a lower cost, higher reliability data, remote access services, and expandable storage space, is received much attention among enterprises individual users. However, providing secure service could be challenging task for some situations, example, how to search encrypted data in IIoT. In this paper, we examine security recent proposed certificateless searchable public key encryption scheme environments...

Internet of Things (IoT) supports high flexibility and convenience in several applications because the IoT devices continuously transfer, share, exchange data without human intervention. During shared or exchanged progress data, security privacy threats result published mainly corresponds to a raw dataset, an attacker can easily obtain details on environment. In paper, we present sanitization approach by adopting hierarchical-cluster method hide confidential information while still...

High-utility itemset mining (HUIM) has been gaining popularity in the field of data mining. Frequent used to be main tool reveal high-frequency patterns but failed consider concept profit. HUIM, on other hand, obtains itemsets and is practical commercial applications. A challenge HUIM that should handle exponential search space for when number distinct items size database are both too large. The existing methods overlook length high-utility itemsets; hence, a large gets an unreasonable...

Incomplete data is one major kind of multi-dimensional dataset that has random-distributed missing nodes in its dimensions. It very difficult to retrieve information from this type when it becomes large. Finding top-k dominant values a challenging procedure. Some algorithms are present enhance process, but most efficient only dealing with small incomplete data. One the make application dominating (TKD) query possible Bitmap Index Guided (BIG) algorithm. This algorithm greatly improves...

Abstract A smart grid (SG) is an advanced power system deployed in a cloud center and meters (at the consumer end) that provides higher reliability, better data protection, improved efficiency, automatic monitoring, effective management of consumption. However, SG also poses certain challenges need to be addressed. For example, provided by meter are time-sensitive cannot handle high latency SG. Moreover, depends on memory, energy, other factors. Besides, security between critical issue needs...

Rapid advancement of industrial internet things (IoT) technology has changed the supply chain network to an open system meet high demand for individualized products and provide better customer experiences. However open-system forced many small midsize enterprises (SMEs) adopt vertical integration by being divided into smaller companies with a distinctive business each SME but central alliance produce range gain competencies. Therefore, existing models do not guarantee protection data privacy...

The Internet of Things (IoT) has revolutionized practically every industry, including agriculture, due to its fast expansion and integration into other industries. application IoT in agriculture motivates farmers use their resources wisely allows for better field monitoring decision-making, resulting increased agricultural productivity. Because IoT-enabled systems need the various types sensors that collect data (such as soil moisture humidity) then transmit it over network. IoT-based...

High utility itemset mining has become an important and critical operation in the Data Mining field. generates more profitable itemsets association among these itemsets, to make business decisions strategies. Although, high is important, it not sole measure decide efficient strategies such as discount offers. It very consider pattern of based on frequency well predict itemsets. For example, a supermarket or restaurant, beverages like champagne wine might generate (profit), but also sell less...

Privacy-preserving data mining has become an interesting and emerging issue in recent years since it can, not only hide the sensitive information but still mine meaningful knowledge at same time. Since privacy-preserving is a non-trivial task, which also concerned as NP-hard problem, several evolutionary algorithms were presented to find optimized solutions most of them focus on considering single-objective function with pre-defined weight values three side effects (<i>hiding failure,...

In Cyber-Physical Systems (CPS), especially in human-in-the-loop situations (also known as HitLCPS), the security and privacy for keeping sensitive information private is considered an emerging topic recent decades. Many techniques privacy-preserving data mining (PPDM) can be applied directly to HitLCPS. However, most of them date have focused on handling singular threshold problems sanitization. If a itemset includes more items, it has higher probability being identified due its...

The Internet of Things (IoT) play an important role in the financial sector recent decades since several stock prediction models can be performed accurately according to IoT-based services. In real-time applications, accuracy price fluctuation forecast is very investors, and it helps investors better manage their funds when formulating trading strategies. It has always been a goal difficult problem for researchers use predictive tools obtain predicted values closer actual from given data...

Abstract Privacy‐preserving data mining (PPDM) is a popular research topic in the field. For individual information protection, it vital to protect sensitive during procedures. Furthermore, also serious offense spill private knowledge. Recently, many PPDM algorithms have been proposed conceal items given database disclose high‐frequency items. These recent methods already proven be excellent protecting confidential and maintaining integrity of input database. All prior techniques, however,...